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Oversight, Consideration of Risks, Says NAM Special Publication","authorsOrOrg":"National Academies Artificial Intelligence","evidenceType":"research_institute","evidenceTypeLabel":"Research institute","url":"https://www.nationalacademies.org/news/capturing-the-potential-of-generative-ais-use-in-health-and-medicine-requires-collaboration-and-oversight-consideration-of-risks-says-nam-special-publication","finding":"NAM special publication on generative AI in health & medicine.","aiGenerated":true,"topicCodes":["compute_reporting","training_data","ai_worker_displacement"],"origin":"promoted"},{"id":"lit-stanford-one-hundred-year-study-on-ai-one-hundred-year","title":"One Hundred Year Study on Artificial Intelligence (AI100)","authorsOrOrg":"Stanford One Hundred Year Study on AI","evidenceType":"research_institute","evidenceTypeLabel":"Research institute","url":"https://ai100.stanford.edu/","finding":"Stanford's standing century-long study of AI's societal impact.","aiGenerated":true,"topicCodes":["compute_reporting","training_data","ai_worker_displacement","deepfakes"],"origin":"promoted"},{"id":"lit-ada-lovelace-institute-measuring-up-ada-lovelace-insti","title":"Measuring up | Ada Lovelace Institute","authorsOrOrg":"Ada Lovelace Institute","evidenceType":"civil_society","evidenceTypeLabel":"Civil society","url":"https://www.adalovelaceinstitute.org/policy-briefing/measuring-up/","finding":"Ada Lovelace Institute policy briefing.","aiGenerated":true,"topicCodes":["compute_reporting","training_data","ai_worker_displacement"],"origin":"promoted"},{"id":"lit-brookings-artificial-intelligence-anthropomorphic-ai-t","title":"Anthropomorphic AI terms create gaps in accountability | Brookings","authorsOrOrg":"Brookings Artificial Intelligence","evidenceType":"think_tank","evidenceTypeLabel":"Think tank","url":"https://www.brookings.edu/articles/anthropomorphic-ai-terms-create-gaps-in-accountability/","finding":"Commentary on how anthropomorphic AI language obscures accountability.","aiGenerated":true,"topicCodes":["compute_reporting","training_data","biometric_id","ai_worker_displacement"],"origin":"promoted"},{"id":"lit-center-for-security-and-emerging-technology-cset-beyon","title":"Beyond P(doom) for AI Risk: Quantifying Uncertainty Without Probability","authorsOrOrg":"Center for Security and Emerging Technology (CSET)","evidenceType":"research_institute","evidenceTypeLabel":"Research institute","url":"https://cset.georgetown.edu/publication/beyond-pdoom-for-ai-risk-quantifying-uncertainty-without-probability/","finding":"Argues AI-risk assessment should characterise structured uncertainty instead of collapsing to a single 'probability of doom' number.","aiGenerated":true,"topicCodes":["catastrophic_risk"],"origin":"promoted"},{"id":"lit-algorithmwatch-policy-brief-our-recommendations-for-st","title":"Policy Brief: Our recommendations for strengthening data access for public interest research","authorsOrOrg":"AlgorithmWatch","evidenceType":"civil_society","evidenceTypeLabel":"Civil society","url":"https://algorithmwatch.org/en/policy-brief-platforms-data-access/","finding":"Recommends stronger platform data-access rules so independent researchers can study automated systems in the public interest.","aiGenerated":true,"topicCodes":["training_data","transparency"],"origin":"promoted"},{"id":"lit-bengio-hinton-yao-song-et-al-managing-extreme-ai-risks","title":"Managing extreme AI risks amid rapid progress","authorsOrOrg":"Bengio, Hinton, Yao, Song, et al.","year":2024,"venue":"Science","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1126/science.adn0117","finding":"Warns \"AI safety research is lagging\" and present governance initiatives \"lack the mechanisms and institutions to prevent misuse and recklessness\", urging adaptive governance plus safety R&D.","aiGenerated":true,"topicCodes":["catastrophic_risk"],"origin":"promoted"},{"id":"lit-shevlane-farquhar-garfinkel-et-al-model-evaluation-for","title":"Model evaluation for extreme risks","authorsOrOrg":"Shevlane, Farquhar, Garfinkel, et al.","year":2023,"venue":"arXiv","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2305.15324","finding":"Proposes \"dangerous capability evaluations\" and alignment evaluations of frontier models so developers and policymakers can make \"responsible decisions about model training, deployment, and security\".","aiGenerated":true,"topicCodes":["catastrophic_risk"],"origin":"promoted"},{"id":"lit-anderljung-barnhart-korinek-et-al-frontier-ai-regulati","title":"Frontier AI Regulation: Managing Emerging Risks to Public Safety","authorsOrOrg":"Anderljung, Barnhart, Korinek, et al.","year":2023,"venue":"arXiv","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2307.03718","finding":"Argues \"industry self-regulation is an important first step\" but \"government intervention will be needed\", proposing safety standards, registration and reporting, and compliance mechanisms.","aiGenerated":true,"topicCodes":["foundation_models","catastrophic_risk"],"origin":"promoted"},{"id":"lit-soice-rocha-cordova-specter-esvelt-can-large-language","title":"Can large language models democratize access to dual-use biotechnology?","authorsOrOrg":"Soice, Rocha, Cordova, Specter, Esvelt","year":2023,"venue":"arXiv","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2306.03809","finding":"Red-team exercise finding LLM chatbots \"may also confer easy access to dual-use technologies capable of inflicting great harm\" and could make pandemic-class agents more widely accessible.","aiGenerated":true,"topicCodes":["catastrophic_risk"],"origin":"promoted"},{"id":"lit-chesney-citron-deep-fakes-a-looming-challenge-for-priv","title":"Deep Fakes: A Looming Challenge for Privacy, Democracy, and National Security","authorsOrOrg":"Chesney & Citron","year":2019,"venue":"California Law Review","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://www.californialawreview.org/print/deep-fakes-a-looming-challenge-for-privacy-democracy-and-national-security","finding":"Maps deepfake harms across privacy, democracy, and national security and evaluates civil, criminal, and regulatory responses as fakes grow \"increasingly resistant to detection\".","aiGenerated":true,"topicCodes":["deepfakes"],"origin":"promoted"},{"id":"lit-vaccari-chadwick-deepfakes-and-disinformation-explorin","title":"Deepfakes and Disinformation: Exploring the Impact of Synthetic Political Video on Deception, Uncertainty, and Trust in News","authorsOrOrg":"Vaccari & Chadwick","year":2020,"venue":"Social Media + Society","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1177/2056305120903408","finding":"Experiment finds people \"are more likely to feel uncertain than to be misled by deepfakes, but this resulting uncertainty, in turn, reduces trust in news on social media\".","aiGenerated":true,"topicCodes":["deepfakes"],"origin":"promoted"},{"id":"lit-groh-sankaranarayanan-singh-kim-lippman-picard-human-d","title":"Human detection of political speech deepfakes across transcripts, audio, and video","authorsOrOrg":"Groh, Sankaranarayanan, Singh, Kim, Lippman, Picard","year":2024,"venue":"Nature Communications","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1038/s41467-024-51998-z","finding":"Experiments show \"audio and visual information enables more accurate discernment than text alone\" — humans rely more on how something is said than on transcript content.","aiGenerated":true,"topicCodes":["deepfakes"],"origin":"promoted"},{"id":"lit-fallis-the-epistemic-threat-of-deepfakes","title":"The Epistemic Threat of Deepfakes","authorsOrOrg":"Fallis","year":2021,"venue":"Philosophy & Technology","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s13347-020-00419-2","finding":"Argues deepfakes pose an epistemic threat because they \"reduce the amount of information that videos carry to viewers\", undermining knowledge acquired from video evidence.","aiGenerated":true,"topicCodes":["deepfakes","synthetic_content_provenance"],"origin":"promoted"},{"id":"lit-acemoglu-restrepo-robots-and-jobs-evidence-from-us-lab","title":"Robots and Jobs: Evidence from US Labor Markets","authorsOrOrg":"Acemoglu & Restrepo","year":2020,"venue":"Journal of Political Economy","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1086/705716","finding":"Estimates \"one more robot per thousand workers reduces the employment-to-population ratio by 0.2 percentage points and wages by 0.42%\" — the displacement evidence policy debates cite.","aiGenerated":true,"topicCodes":["ai_worker_displacement"],"origin":"promoted"},{"id":"lit-frey-osborne-the-future-of-employment-how-susceptible","title":"The future of employment: How susceptible are jobs to computerisation?","authorsOrOrg":"Frey & Osborne","year":2017,"venue":"Technological Forecasting and Social Change","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1016/j.techfore.2016.08.019","finding":"Estimates computerisation probabilities for 702 occupations, finding about 47% of total US employment \"at risk\" — the headline figure framing displacement and retraining policy.","aiGenerated":true,"topicCodes":["ai_worker_displacement","employment"],"origin":"promoted"},{"id":"lit-eloundou-manning-mishkin-rock-gpts-are-gpts-labor-mark","title":"GPTs are GPTs: Labor market impact potential of LLMs","authorsOrOrg":"Eloundou, Manning, Mishkin, Rock","year":2024,"venue":"Science","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1126/science.adj0998","finding":"Finds around 80% of the U.S. workforce \"could have at least 10% of their work tasks affected\" by LLMs, which exhibit \"traits of general-purpose technologies\".","aiGenerated":true,"topicCodes":["ai_worker_displacement","foundation_models"],"origin":"promoted"},{"id":"lit-de-stefano-negotiating-the-algorithm-automation-artifi","title":"\"Negotiating the algorithm\": Automation, artificial intelligence and labour protection","authorsOrOrg":"De Stefano","year":2018,"venue":"ILO Employment Working Paper No. 246","evidenceType":"working_paper","evidenceTypeLabel":"Working paper","url":"https://www.ilo.org/publications/negotiating-algorithm-automation-artificial-intelligence-and-labour","finding":"Argues labour law must protect worker dignity under algorithmic management, urging a \"human-in-command approach\" with social partners governing automation.","aiGenerated":true,"topicCodes":["ai_worker_displacement","employment"],"origin":"promoted"},{"id":"lit-mitchell-wu-zaldivar-et-al-model-cards-for-model-repor","title":"Model Cards for Model Reporting","authorsOrOrg":"Mitchell, Wu, Zaldivar, et al.","year":2019,"venue":"ACM FAT* '19","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3287560.3287596","finding":"Proposes \"model cards\" — short documents accompanying trained models with benchmarked evaluation across conditions — the template transparency mandates reference.","aiGenerated":true,"topicCodes":["transparency"],"origin":"promoted"},{"id":"lit-gebru-morgenstern-vecchione-et-al-datasheets-for-datas","title":"Datasheets for Datasets","authorsOrOrg":"Gebru, Morgenstern, Vecchione, et al.","year":2021,"venue":"Communications of the ACM","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3458723","finding":"Proposes \"that every dataset be accompanied with a datasheet that documents its motivation, composition, collection process, recommended uses\" for transparency and accountability.","aiGenerated":true,"topicCodes":["transparency","training_data"],"origin":"promoted"},{"id":"lit-wachter-mittelstadt-floridi-why-a-right-to-explanation","title":"Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation","authorsOrOrg":"Wachter, Mittelstadt & Floridi","year":2017,"venue":"International Data Privacy Law","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1093/idpl/ipx005","finding":"Argues the GDPR mandates only \"meaningful, but properly limited, information\" about automated decisions — a right to be informed, not a right to explanation of specific decisions.","aiGenerated":true,"topicCodes":["transparency","redress"],"origin":"promoted"},{"id":"lit-ananny-crawford-seeing-without-knowing-limitations-of","title":"Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability","authorsOrOrg":"Ananny & Crawford","year":2018,"venue":"New Media & Society","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1177/1461444816676645","finding":"Critiques accountability models resting on \"ideals and logics of transparency\", presenting ten limitations of transparency as a route to algorithmic accountability.","aiGenerated":true,"topicCodes":["transparency"],"origin":"promoted"},{"id":"lit-bommasani-et-al-on-the-opportunities-and-risks-of-foun","title":"On the Opportunities and Risks of Foundation Models","authorsOrOrg":"Bommasani et al.","year":2021,"venue":"arXiv","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2108.07258","finding":"Defines foundation models and warns homogenization \"demands caution, as the defects of the foundation model are inherited by all the adapted models downstream\".","aiGenerated":true,"topicCodes":["foundation_models"],"origin":"promoted"},{"id":"lit-hacker-engel-mauer-regulating-chatgpt-and-other-large","title":"Regulating ChatGPT and other Large Generative AI Models","authorsOrOrg":"Hacker, Engel & Mauer","year":2023,"venue":"ACM FAccT '23","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3593013.3594067","finding":"Argues AI regulation \"has primarily focused on conventional AI models, not LGAIMs\" and should target \"concrete high-risk applications, and not the pre-trained model itself\".","aiGenerated":true,"topicCodes":["foundation_models"],"origin":"promoted"},{"id":"lit-gutierrez-aguirre-uuk-boine-franklin-a-proposal-for-a","title":"A Proposal for a Definition of General Purpose Artificial Intelligence Systems","authorsOrOrg":"Gutierrez, Aguirre, Uuk, Boine & Franklin","year":2023,"venue":"Digital Society","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s44206-023-00068-w","finding":"Finds existing GPAIS definitions \"do not provide sufficient guidance\" and proposes \"a functional definition of the term that facilitates its governance within the EU\".","aiGenerated":true,"topicCodes":["foundation_models"],"origin":"promoted"},{"id":"lit-buolamwini-gebru-gender-shades-intersectional-accuracy","title":"Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification","authorsOrOrg":"Buolamwini & Gebru","year":2018,"venue":"PMLR (FAT* 2018)","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://proceedings.mlr.press/v81/buolamwini18a.html","finding":"Audit of commercial classifiers showing \"darker-skinned females are the most misclassified group (with error rates of up to 34.7%)\" versus 0.8% for lighter-skinned males.","aiGenerated":true,"topicCodes":["biometric_id"],"origin":"promoted"},{"id":"lit-grother-ngan-hanaoka-nist-face-recognition-vendor-test","title":"Face Recognition Vendor Test (FRVT) Part 3: Demographic Effects","authorsOrOrg":"Grother, Ngan & Hanaoka (NIST)","year":2019,"venue":"NISTIR 8280","evidenceType":"research_institute","evidenceTypeLabel":"Research institute","url":"https://doi.org/10.6028/NIST.IR.8280","finding":"Cross-algorithm benchmark finding false-positive differentials \"vary by factors of 10 to beyond 100 times\" across demographics — the empirical basis for accuracy-disparity rules.","aiGenerated":true,"topicCodes":["biometric_id"],"origin":"promoted"},{"id":"lit-almeida-shmarko-lomas-the-ethics-of-facial-recognition","title":"The ethics of facial recognition technologies, surveillance, and accountability in an age of artificial intelligence","authorsOrOrg":"Almeida, Shmarko & Lomas","year":2022,"venue":"AI and Ethics","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s43681-021-00077-w","finding":"Comparative US/EU/UK analysis concluding \"there is no standardised human rights framework and regulatory requirements that can be easily applied to FRT rollout\".","aiGenerated":true,"topicCodes":["biometric_id"],"origin":"promoted"},{"id":"lit-raposo-the-use-of-facial-recognition-technology-by-law","title":"The Use of Facial Recognition Technology by Law Enforcement in Europe: a Non-Orwellian Draft Proposal","authorsOrOrg":"Raposo","year":2023,"venue":"European Journal on Criminal Policy and Research","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s10610-022-09512-y","finding":"Argues the EU framework already contains norms \"directly or indirectly applicable to facial recognition\" in policing, and drafts a dedicated rights-protective law for its use.","aiGenerated":true,"topicCodes":["biometric_id","criminal_justice"],"origin":"promoted"},{"id":"lit-sastry-heim-belfield-anderljung-brundage-et-al-computi","title":"Computing Power and the Governance of Artificial Intelligence","authorsOrOrg":"Sastry, Heim, Belfield, Anderljung, Brundage, et al.","year":2024,"venue":"arXiv","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2402.08797","finding":"Argues compute is a uniquely governable lever because it is \"detectable, excludable, and quantifiable, and is produced via an extremely concentrated supply chain\".","aiGenerated":true,"topicCodes":["compute_export_controls","compute_reporting","sovereign_ai"],"origin":"promoted"},{"id":"lit-heim-koessler-training-compute-thresholds-features-and","title":"Training Compute Thresholds: Features and Functions in AI Regulation","authorsOrOrg":"Heim & Koessler","year":2024,"venue":"arXiv","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2405.10799","finding":"Finds \"training compute currently is the most suitable metric to identify GPAI models\", but thresholds should only trigger further scrutiny, not determine risk measures alone.","aiGenerated":true,"topicCodes":["compute_reporting"],"origin":"promoted"},{"id":"lit-shavit-what-does-it-take-to-catch-a-chinchilla-verifyi","title":"What does it take to catch a Chinchilla? Verifying Rules on Large-Scale Neural Network Training via Compute Monitoring","authorsOrOrg":"Shavit","year":2023,"venue":"arXiv","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2303.11341","finding":"Proposes chip-level monitoring (on-chip logging, supply-chain oversight) giving governments \"high confidence that no actor uses large quantities of specialized ML chips\" in violation of rules.","aiGenerated":true,"topicCodes":["compute_reporting"],"origin":"promoted"},{"id":"lit-lehdonvirta-w-hawkins-compute-north-vs-compute-south-t","title":"Compute North vs. Compute South: The Uneven Possibilities of Compute-based AI Governance Around the Globe","authorsOrOrg":"Lehdonvirta, Wú & Hawkins","year":2024,"venue":"AIES Proceedings","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1609/aies.v7i1.31683","finding":"Census of hyperscale cloud regions shows a divide between \"Compute North\" states hosting training-relevant compute and a Compute South, shaping who can wield compute-based governance.","aiGenerated":true,"topicCodes":["compute_reporting","development_rights_framing","sovereign_ai"],"origin":"promoted"},{"id":"lit-margoni-kretschmer-a-deeper-look-into-the-eu-text-and","title":"A Deeper Look into the EU Text and Data Mining Exceptions: Harmonisation, Data Ownership, and the Future of Technology","authorsOrOrg":"Margoni & Kretschmer","year":2022,"venue":"GRUR International","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1093/grurint/ikac054","finding":"Critiques the EU TDM regime: \"an excessively broad definition of TDM\" makes data-driven AI development dependent on an exception, with narrow beneficiaries and lawful-access hurdles.","aiGenerated":true,"topicCodes":["training_data"],"origin":"promoted"},{"id":"lit-henderson-li-jurafsky-hashimoto-lemley-liang-foundatio","title":"Foundation Models and Fair Use","authorsOrOrg":"Henderson, Li, Jurafsky, Hashimoto, Lemley & Liang","year":2023,"venue":"Journal of Machine Learning Research","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://jmlr.org/papers/v24/23-0569.html","finding":"Shows foundation models \"are trained on copyrighted material\" and warns \"fair use is not guaranteed\", urging technical mitigations to keep training and deployment within fair use.","aiGenerated":true,"topicCodes":["training_data","foundation_models"],"origin":"promoted"},{"id":"lit-novelli-casolari-hacker-spedicato-floridi-generative-a","title":"Generative AI in EU law: Liability, privacy, intellectual property, and cybersecurity","authorsOrOrg":"Novelli, Casolari, Hacker, Spedicato & Floridi","year":2024,"venue":"Computer Law & Security Review","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1016/j.clsr.2024.106066","finding":"Examines how the EU AI Act, liability regimes, GDPR, copyright and cybersecurity rules apply to generative AI, identifying gaps and proposing targeted regulatory refinements.","aiGenerated":true,"topicCodes":["training_data","foundation_models"],"origin":"promoted"},{"id":"lit-longpre-mahari-et-al-data-provenance-initiative-a-larg","title":"A large-scale audit of dataset licensing and attribution in AI","authorsOrOrg":"Longpre, Mahari, et al. (Data Provenance Initiative)","year":2024,"venue":"Nature Machine Intelligence","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1038/s42256-024-00878-8","finding":"Audit of 1,800+ AI training datasets finds \"licence omission rates of more than 70% and error rates of more than 50%\" on popular hosting sites.","aiGenerated":true,"topicCodes":["training_data"],"origin":"promoted"},{"id":"lit-obermeyer-powers-vogeli-mullainathan-dissecting-racial","title":"Dissecting racial bias in an algorithm used to manage the health of populations","authorsOrOrg":"Obermeyer, Powers, Vogeli & Mullainathan","year":2019,"venue":"Science","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1126/science.aax2342","finding":"A widely used US care-management algorithm is racially biased — \"at a given risk score, Black patients are considerably sicker\" — because it predicts costs, not illness.","aiGenerated":true,"topicCodes":["healthcare"],"origin":"promoted"},{"id":"lit-gerke-babic-evgeniou-cohen-the-need-for-a-system-view","title":"The need for a system view to regulate artificial intelligence/machine learning-based software as medical device","authorsOrOrg":"Gerke, Babic, Evgeniou & Cohen","year":2020,"venue":"npj Digital Medicine","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1038/s41746-020-0262-2","finding":"Argues regulators of adaptive AI/ML medical software must shift from a product-centric approach to \"a system view\" covering human-AI interaction and organizational context.","aiGenerated":true,"topicCodes":["healthcare"],"origin":"promoted"},{"id":"lit-wu-wu-daneshjou-ouyang-ho-zou-how-medical-ai-devices-a","title":"How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals","authorsOrOrg":"Wu, Wu, Daneshjou, Ouyang, Ho & Zou","year":2021,"venue":"Nature Medicine","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1038/s41591-021-01312-x","finding":"Audit of 130 FDA-approved medical AI devices finds evaluation gaps — mostly retrospective, scant multi-site testing — \"that can mask vulnerabilities of devices when they are deployed on patients\".","aiGenerated":true,"topicCodes":["healthcare"],"origin":"promoted"},{"id":"lit-muehlematter-daniore-vokinger-approval-of-artificial-i","title":"Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015–20): a comparative analysis","authorsOrOrg":"Muehlematter, Daniore & Vokinger","year":2021,"venue":"The Lancet Digital Health","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1016/S2589-7500(20)30292-2","finding":"Maps 222 US- and 240 EU-approved AI/ML medical devices (2015–20); of 124 approved in both regions, 80 were first approved in Europe — grounding pathway-stringency debates.","aiGenerated":true,"topicCodes":["healthcare"],"origin":"promoted"},{"id":"lit-chouldechova-fair-prediction-with-disparate-impact-a-s","title":"Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments","authorsOrOrg":"Chouldechova","year":2017,"venue":"Big Data","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1089/big.2016.0047","finding":"Shows a recidivism instrument satisfying predictive parity \"may lead to considerable disparate impact when recidivism prevalence differs across groups\".","aiGenerated":true,"topicCodes":["criminal_justice"],"origin":"promoted"},{"id":"lit-kleinberg-mullainathan-raghavan-inherent-trade-offs-in","title":"Inherent Trade-Offs in the Fair Determination of Risk Scores","authorsOrOrg":"Kleinberg, Mullainathan & Raghavan","year":2017,"venue":"ITCS 2017","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://arxiv.org/abs/1609.05807","finding":"Proves calibration and balanced error rates cannot coexist: \"except in highly constrained special cases, there is no method that can satisfy these three conditions simultaneously\".","aiGenerated":true,"topicCodes":["criminal_justice"],"origin":"promoted"},{"id":"lit-dressel-farid-the-accuracy-fairness-and-limits-of-pred","title":"The accuracy, fairness, and limits of predicting recidivism","authorsOrOrg":"Dressel & Farid","year":2018,"venue":"Science Advances","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1126/sciadv.aao5580","finding":"Finds COMPAS \"is no more accurate or fair than predictions made by people with little or no criminal justice expertise\"; a two-feature linear model matches it.","aiGenerated":true,"topicCodes":["criminal_justice"],"origin":"promoted"},{"id":"lit-berk-heidari-jabbari-kearns-roth-fairness-in-criminal","title":"Fairness in Criminal Justice Risk Assessments: The State of the Art","authorsOrOrg":"Berk, Heidari, Jabbari, Kearns & Roth","year":2018,"venue":"Sociological Methods & Research","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1177/0049124118782533","finding":"Surveys six fairness definitions: \"impossible to maximize accuracy and fairness at the same time, and impossible simultaneously to satisfy all kinds of fairness\".","aiGenerated":true,"topicCodes":["criminal_justice"],"origin":"promoted"},{"id":"lit-weber-wulff-anohina-naumeca-bjelobaba-et-al-testing-of","title":"Testing of detection tools for AI-generated text","authorsOrOrg":"Weber-Wulff, Anohina-Naumeca, Bjelobaba, et al.","year":2023,"venue":"International Journal for Educational Integrity","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s40979-023-00146-z","finding":"Systematic testing showed \"available detection tools are neither accurate nor reliable\" and biased toward classing AI text as human-written — fragile ground for misconduct sanctions.","aiGenerated":true,"topicCodes":["education"],"origin":"promoted"},{"id":"lit-liang-yuksekgonul-mao-wu-zou-gpt-detectors-are-biased","title":"GPT detectors are biased against non-native English writers","authorsOrOrg":"Liang, Yuksekgonul, Mao, Wu & Zou","year":2023,"venue":"Patterns","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1016/j.patter.2023.100779","finding":"Finds \"GPT detectors are biased against non-native English writers\", frequently misclassifying their writing as AI-generated — a fairness flaw in detector-backed integrity policies.","aiGenerated":true,"topicCodes":["education"],"origin":"promoted"},{"id":"lit-chan-a-comprehensive-ai-policy-education-framework-for","title":"A comprehensive AI policy education framework for university teaching and learning","authorsOrOrg":"Chan","year":2023,"venue":"International Journal of Educational Technology in Higher Education","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1186/s41239-023-00408-3","finding":"Surveys of 457 students and 180 staff ground an \"AI Ecological Education Policy Framework\" spanning pedagogical, governance and operational dimensions.","aiGenerated":true,"topicCodes":["education"],"origin":"promoted"},{"id":"lit-unesco-miao-holmes-guidance-for-generative-ai-in-educa","title":"Guidance for generative AI in education and research","authorsOrOrg":"UNESCO (Miao & Holmes)","year":2023,"venue":"UNESCO","evidenceType":"research_institute","evidenceTypeLabel":"Research institute","url":"https://doi.org/10.54675/EWZM9535","finding":"First global guidance urging governments to regulate GenAI in education, mandating \"the protection of data privacy\" and age limits for independent GenAI conversations.","aiGenerated":true,"topicCodes":["education"],"origin":"promoted"},{"id":"lit-ho-barnhart-trager-bengio-et-al-international-institut","title":"International Institutions for Advanced AI","authorsOrOrg":"Ho, Barnhart, Trager, Bengio, et al.","year":2023,"venue":"arXiv","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2307.04699","finding":"Proposes four international institutional models for advanced AI: a Commission on Frontier AI, an Advanced AI Governance Organization, a Frontier AI Collaborative, and an AI Safety Project.","aiGenerated":true,"topicCodes":["international_coordination"],"origin":"promoted"},{"id":"lit-roberts-hine-taddeo-floridi-global-ai-governance-barri","title":"Global AI governance: barriers and pathways forward","authorsOrOrg":"Roberts, Hine, Taddeo & Floridi","year":2024,"venue":"International Affairs","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1093/ia/iiae073","finding":"Diagnoses a global AI governance deficit and, weighing new centralized institutions against coordinating existing ones, recommends foregrounding the OECD as the centre for AI policy expertise.","aiGenerated":true,"topicCodes":["international_coordination"],"origin":"promoted"},{"id":"lit-tallberg-erman-furendal-geith-klamberg-lundgren-the-gl","title":"The Global Governance of Artificial Intelligence: Next Steps for Empirical and Normative Research","authorsOrOrg":"Tallberg, Erman, Furendal, Geith, Klamberg & Lundgren","year":2023,"venue":"International Studies Review","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1093/isr/viad040","finding":"Maps global AI governance and sets a dual agenda: \"an empirical approach, aimed at mapping and explaining\" it and \"a normative approach, aimed at developing and applying standards\".","aiGenerated":true,"topicCodes":["international_coordination"],"origin":"promoted"},{"id":"lit-schmitt-mapping-global-ai-governance-a-nascent-regime","title":"Mapping global AI governance: a nascent regime in a fragmented landscape","authorsOrOrg":"Schmitt","year":2022,"venue":"AI and Ethics","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s43681-021-00083-y","finding":"Maps a nascent, \"polycentric and fragmented\" AI governance regime in which the OECD holds \"considerable epistemic authority and norm-setting power\".","aiGenerated":true,"topicCodes":["international_coordination"],"origin":"promoted"},{"id":"lit-manish-raghavan-solon-barocas-jon-kleinberg-karen-levy","title":"Mitigating Bias in Algorithmic Hiring: Evaluating Claims and Practices","authorsOrOrg":"Manish Raghavan, Solon Barocas, Jon Kleinberg, Karen Levy","year":2020,"venue":"ACM FAT* '20","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3351095.3372828","finding":"Survey of algorithmic employment-assessment vendors' bias-mitigation claims, examining how \"algorithmic de-biasing techniques interface with, and create challenges for, antidiscrimination law\".","aiGenerated":true,"topicCodes":["employment"],"origin":"promoted"},{"id":"lit-lucas-wright-roxana-mika-muenster-briana-vecchione-tia","title":"Null Compliance: NYC Local Law 144 and the Challenges of Algorithm Accountability","authorsOrOrg":"Lucas Wright, Roxana Mika Muenster, Briana Vecchione, Tianyao Qu, Pika (Senhuang) Cai, COMM/INFO 2450 Student Investigators, Jacob Metcalf, J. Nathan Matias","year":2024,"venue":"ACM FAccT '24","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3630106.3658998","finding":"Field study of 391 NYC employers under LL 144: only 18 posted bias-audit reports; employer discretion over scope yields \"null compliance\", blunting the first AEDT bias-audit mandate.","aiGenerated":true,"topicCodes":["employment"],"origin":"promoted"},{"id":"lit-lara-groves-jacob-metcalf-alayna-kennedy-briana-vecchi","title":"Auditing Work: Exploring the New York City Algorithmic Bias Audit Regime","authorsOrOrg":"Lara Groves, Jacob Metcalf, Alayna Kennedy, Briana Vecchione, Andrew Strait","year":2024,"venue":"ACM FAccT '24","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3630106.3658959","finding":"From qualitative interviews with 16 experts and practitioners, finds \"LL 144 has not effectively established an auditing regime\": undefined key terms, auditor data-access barriers, contested auditor roles.","aiGenerated":true,"topicCodes":["employment"],"origin":"promoted"},{"id":"lit-jeremias-adams-prassl-regulating-algorithms-at-work-le","title":"Regulating Algorithms at Work: Lessons for a 'European Approach to Artificial Intelligence'","authorsOrOrg":"Jeremias Adams-Prassl","year":2022,"venue":"European Labour Law Journal","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1177/20319525211062558","finding":"Surveys EU data-protection, non-discrimination and social-acquis rules for governing \"automated systems in high-risk settings such as the workplace\", drawing lessons for the proposed EU AI Act.","aiGenerated":true,"topicCodes":["employment"],"origin":"promoted"},{"id":"lit-sandra-wachter-brent-mittelstadt-chris-russell-counter","title":"Counterfactual Explanations Without Opening the Black Box: Automated Decisions and the GDPR","authorsOrOrg":"Sandra Wachter, Brent Mittelstadt, Chris Russell","year":2018,"venue":"Harvard Journal of Law & Technology","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://arxiv.org/abs/1711.00399","finding":"Proposes counterfactual explanations — \"the smallest change to the world that can be made to obtain a desirable outcome\" — to help individuals understand, contest and alter automated decisions.","aiGenerated":true,"topicCodes":["redress"],"origin":"promoted"},{"id":"lit-henrietta-lyons-eduardo-velloso-tim-miller-conceptuali","title":"Conceptualising Contestability: Perspectives on Contesting Algorithmic Decisions","authorsOrOrg":"Henrietta Lyons, Eduardo Velloso, Tim Miller","year":2021,"venue":"PACM HCI (CSCW)","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3449180","finding":"Analysing public submissions on Australia's AI Ethics Framework, treats contesting algorithmic decisions as \"an important safeguard for individuals\" and maps what contestability should require.","aiGenerated":true,"topicCodes":["redress"],"origin":"promoted"},{"id":"lit-kars-alfrink-ianus-keller-gerd-kortuem-neelke-doorn-co","title":"Contestable AI by Design: Towards a Framework","authorsOrOrg":"Kars Alfrink, Ianus Keller, Gerd Kortuem, Neelke Doorn","year":2023,"venue":"Minds and Machines","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s11023-022-09611-z","finding":"Synthesises contestable-AI research into a generative design framework for AI systems that are \"responsive to human intervention throughout the system lifecycle\".","aiGenerated":true,"topicCodes":["redress"],"origin":"promoted"},{"id":"lit-oecd-a-blueprint-for-building-national-compute-capacit","title":"A blueprint for building national compute capacity for artificial intelligence","authorsOrOrg":"OECD","year":2023,"venue":"OECD Digital Economy Papers","evidenceType":"research_institute","evidenceTypeLabel":"Research institute","url":"https://doi.org/10.1787/876367e3-en","finding":"Finds 'no country today has data on, or a targeted plan for, national AI compute capacity' and offers the first policy blueprint across capacity, effectiveness, and resilience.","aiGenerated":true,"topicCodes":["sovereign_ai"],"origin":"promoted"},{"id":"lit-sophie-bennani-taylor-infrastructuring-ai-the-stabiliz","title":"Infrastructuring AI: The stabilization of 'artificial intelligence' in and beyond national AI strategies","authorsOrOrg":"Sophie Bennani-Taylor","year":2024,"venue":"First Monday","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.5210/fm.v29i2.13568","finding":"Shows the UK National AI Strategy 'stabilises: AI as an autonomous and inevitable force', revealing how national strategies fix actors, capital flows, and power relations.","aiGenerated":true,"topicCodes":["sovereign_ai"],"origin":"promoted"},{"id":"lit-jakob-edler-knut-blind-henning-kroll-torben-schubert-t","title":"Technology sovereignty as an emerging frame for innovation policy. Defining rationales, ends and means","authorsOrOrg":"Jakob Edler, Knut Blind, Henning Kroll, Torben Schubert","year":2023,"venue":"Research Policy","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1016/j.respol.2023.104765","finding":"Proposes 'a concise yet nuanced concept of technology sovereignty' for innovation policy amid geopolitical competition, explicitly distinguishing it from costly 'near autarky'.","aiGenerated":true,"topicCodes":["tech_sovereignty"],"origin":"promoted"},{"id":"lit-julia-pohle-thorsten-thiel-digital-sovereignty","title":"Digital sovereignty","authorsOrOrg":"Julia Pohle, Thorsten Thiel","year":2020,"venue":"Internet Policy Review","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.14763/2020.4.1532","finding":"Traces how the contested concept is now understood 'more as a discursive practice in politics and policy than as a legal or organisational concept' in digital policy debates.","aiGenerated":true,"topicCodes":["tech_sovereignty"],"origin":"promoted"},{"id":"lit-luciano-floridi-the-fight-for-digital-sovereignty-what","title":"The Fight for Digital Sovereignty: What It Is, and Why It Matters, Especially for the EU","authorsOrOrg":"Luciano Floridi","year":2020,"venue":"Philosophy & Technology","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s13347-020-00423-6","finding":"Five case studies argue digital sovereignty 'affects everyone, whether digital users or not' and make 'the case for a hybrid system of control' with democratic legitimacy for the EU.","aiGenerated":true,"topicCodes":["tech_sovereignty"],"origin":"promoted"},{"id":"lit-andreas-baur-european-dreams-of-the-cloud-imagining-in","title":"European Dreams of the Cloud: Imagining Innovation and Political Control","authorsOrOrg":"Andreas Baur","year":2024,"venue":"Geopolitics","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1080/14650045.2022.2151902","finding":"Analysis of GAIA-X, Bundescloud and Microsoft's EU cloud reveals 'a performative coupling of innovation and political ideas of control, territoriality and sovereignty'.","aiGenerated":true,"topicCodes":["tech_sovereignty"],"origin":"promoted"},{"id":"lit-marie-therese-png-at-the-tensions-of-south-and-north-c","title":"At the Tensions of South and North: Critical Roles of Global South Stakeholders in AI Governance","authorsOrOrg":"Marie-Therese Png","year":2022,"venue":"ACM FAccT","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3531146.3533200","finding":"Maps Global South-centred AI-governance discourse and the paradox of participation, offering 'three roles for Global South actors to substantively engage in AI governance processes.'","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"},{"id":"lit-shakir-mohamed-marie-therese-png-william-isaac-decolon","title":"Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence","authorsOrOrg":"Shakir Mohamed, Marie-Therese Png, William Isaac","year":2020,"venue":"Philosophy & Technology","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s13347-020-00405-8","finding":"Argues 'post-colonial and decolonial theories' should shape AI's advance as sociotechnical foresight, proposing critical technical practice and reverse tutelage to protect vulnerable populations.","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"},{"id":"lit-nick-couldry-ulises-a-mejias-data-colonialism-rethinki","title":"Data Colonialism: Rethinking Big Data's Relation to the Contemporary Subject","authorsOrOrg":"Nick Couldry, Ulises A. Mejias","year":2019,"venue":"Television & New Media","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1177/1527476418796632","finding":"Theorizes 'data colonialism' as a new extractive order that normalizes appropriating human life through 'data relations,' enabling 'the capitalization of life without limit.'","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"},{"id":"lit-sakiko-fukuda-parr-elizabeth-gibbons-emerging-consensu","title":"Emerging Consensus on 'Ethical AI': Human Rights Critique of Stakeholder Guidelines","authorsOrOrg":"Sakiko Fukuda-Parr, Elizabeth Gibbons","year":2021,"venue":"Global Policy","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1111/1758-5899.12965","finding":"Human-rights audit of 15 'ethical AI' guidelines finds they create 'a set of de facto norms' that re-interpret human rights, are weak on inequality, and lack enforceable accountability.","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"},{"id":"lit-maria-tzanou-plixavra-vogiatzoglou-national-security-a","title":"National Security and New Forms of Surveillance: From the Data Retention Saga to a Data Subject Centred Approach","authorsOrOrg":"Maria Tzanou, Plixavra Vogiatzoglou","year":2025,"venue":"European Papers","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://www.europeanpapers.eu/e-journal/national-security-forms-surveillance-data-retention-saga-data-subject-centred-approach","finding":"Argues the CJEU's controller-based route for applying EU law to national-security surveillance 'creates significant legal uncertainties,' proposing a data-subject-focused scope instead.","aiGenerated":true,"topicCodes":["national_security_carveouts"],"origin":"promoted"},{"id":"lit-daragh-murray-pete-fussey-bulk-surveillance-in-the-dig","title":"Bulk Surveillance in the Digital Age: Rethinking the Human Rights Law Approach to Bulk Monitoring of Communications Data","authorsOrOrg":"Daragh Murray, Pete Fussey","year":2019,"venue":"Israel Law Review","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1017/S0021223718000304","finding":"Contends 'utility and harm calculations can conceal the complex nature of contemporary digital surveillance practices,' rethinking human-rights-law tests for bulk communications surveillance.","aiGenerated":true,"topicCodes":["national_security_carveouts"],"origin":"promoted"},{"id":"lit-rosamund-powell-centre-for-emerging-technology-and-sec","title":"The EU AI Act: National Security Implications (CETaS Explainer)","authorsOrOrg":"Rosamund Powell (Centre for Emerging Technology and Security, Alan Turing Institute)","year":2024,"venue":"CETaS (Alan Turing Institute)","evidenceType":"research_institute","evidenceTypeLabel":"Research institute","url":"https://cetas.turing.ac.uk/sites/default/files/2024-07/cetas_explainer_-_the_eu_ai_act_-_national_security_implications.pdf","finding":"Explains the AI Act's national-security exclusion 'does not apply to any dual-use technologies that are also used outside of the national security context,' and that rights groups dispute it.","aiGenerated":true,"topicCodes":["national_security_carveouts"],"origin":"promoted"},{"id":"lit-chris-jones-romain-lanneau-statewatch-cop-out-security","title":"Cop out: security exemptions in the Artificial Intelligence Act (in: Automating Authority — AI in European police and border regimes)","authorsOrOrg":"Chris Jones, Romain Lanneau (Statewatch)","year":2025,"venue":"Statewatch","evidenceType":"civil_society","evidenceTypeLabel":"Civil society","url":"https://www.statewatch.org/automating-authority-artificial-intelligence-in-european-police-and-border-regimes/2-cop-out-security-exemptions-in-the-artificial-intelligence-act/","finding":"Documents how AI Act security exemptions plus police powers to restrict supervisory information-sharing will make meaningful supervision of policing and migration AI 'extremely difficult.'","aiGenerated":true,"topicCodes":["national_security_carveouts"],"origin":"promoted"},{"id":"lit-alan-chan-carson-ezell-max-kaufmann-kevin-wei-lewis-ha","title":"Visibility into AI Agents","authorsOrOrg":"Alan Chan, Carson Ezell, Max Kaufmann, Kevin Wei, Lewis Hammond, Herbie Bradley, Emma Bluemke, Nitarshan Rajkumar, David Krueger, Noam Kolt, Lennart Heim, Markus Anderljung","year":2024,"venue":"ACM FAccT","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3630106.3658948","finding":"Proposes agent identifiers, real-time monitoring and activity logs to give governance actors visibility — \"where, why, how, and by whom certain AI agents are used.\"","aiGenerated":true,"topicCodes":["agentic_systems_governance"],"origin":"promoted"},{"id":"lit-noam-kolt-governing-ai-agents","title":"Governing AI Agents","authorsOrOrg":"Noam Kolt","year":2025,"venue":"Notre Dame Law Review (forthcoming)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2501.07913","finding":"Uses \"agency law and theory to identify and characterize problems arising from AI agents\" and proposes governance infrastructure built on inclusivity, visibility, and liability.","aiGenerated":true,"topicCodes":["agentic_systems_governance"],"origin":"promoted"},{"id":"lit-alan-chan-kevin-wei-sihao-huang-nitarshan-rajkumar-eli","title":"Infrastructure for AI Agents","authorsOrOrg":"Alan Chan, Kevin Wei, Sihao Huang, Nitarshan Rajkumar, Elija Perrier, Seth Lazar, Gillian K. Hadfield, Markus Anderljung","year":2025,"venue":"Transactions on Machine Learning Research","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://arxiv.org/abs/2501.10114","finding":"Proposes \"agent infrastructure\": external technical systems for attributing actions \"to specific agents, their users, or other actors,\" shaping interactions, and remediating harms.","aiGenerated":true,"topicCodes":["agentic_systems_governance"],"origin":"promoted"},{"id":"lit-lewis-hammond-alan-chan-jesse-clifton-et-al-cooperativ","title":"Multi-Agent Risks from Advanced AI","authorsOrOrg":"Lewis Hammond, Alan Chan, Jesse Clifton, et al. (Cooperative AI Foundation)","year":2025,"venue":"Cooperative AI Foundation","evidenceType":"research_institute","evidenceTypeLabel":"Research institute","url":"https://arxiv.org/abs/2502.14143","finding":"Identifies three failure modes of advanced multi-agent systems — \"miscoordination, conflict, and collusion\" — plus seven risk factors, posing challenges distinct from single-agent AI.","aiGenerated":true,"topicCodes":["agentic_systems_governance"],"origin":"promoted"},{"id":"lit-sayash-kapoor-rishi-bommasani-kevin-klyman-shayne-long","title":"On the Societal Impact of Open Foundation Models","authorsOrOrg":"Sayash Kapoor, Rishi Bommasani, Kevin Klyman, Shayne Longpre, et al.","year":2024,"venue":"arXiv","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2403.07918","finding":"Proposes a marginal-risk framework, finding current research \"insufficient to effectively characterize the marginal risk of open foundation models relative to pre-existing technologies.\"","aiGenerated":true,"topicCodes":["open_weight_release"],"origin":"promoted"},{"id":"lit-irene-solaiman-the-gradient-of-generative-ai-release-m","title":"The Gradient of Generative AI Release: Methods and Considerations","authorsOrOrg":"Irene Solaiman","year":2023,"venue":"ACM FAccT","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3593013.3593981","finding":"Maps six access levels for generative AI where \"each level, from fully closed to fully open, can be viewed as an option along a gradient,\" grounding release-policy tradeoffs.","aiGenerated":true,"topicCodes":["open_weight_release"],"origin":"promoted"},{"id":"lit-elizabeth-seger-noemi-dreksler-richard-moulange-et-al","title":"Open-Sourcing Highly Capable Foundation Models: An evaluation of risks, benefits, and alternative methods for pursuing open-source objectives","authorsOrOrg":"Elizabeth Seger, Noemi Dreksler, Richard Moulange, et al. (Centre for the Governance of AI)","year":2023,"venue":"Centre for the Governance of AI","evidenceType":"research_institute","evidenceTypeLabel":"Research institute","url":"https://arxiv.org/abs/2311.09227","finding":"Argues that for some highly capable models \"open-sourcing may pose sufficiently extreme risks to outweigh the benefits,\" and evaluates alternative routes to open-source objectives.","aiGenerated":true,"topicCodes":["open_weight_release"],"origin":"promoted"},{"id":"lit-rishi-bommasani-sayash-kapoor-kevin-klyman-shayne-long","title":"Considerations for governing open foundation models","authorsOrOrg":"Rishi Bommasani, Sayash Kapoor, Kevin Klyman, Shayne Longpre, Ashwin Ramaswami, Daniel Zhang, Marietje Schaake, Daniel E. Ho, Arvind Narayanan, Percy Liang","year":2024,"venue":"Science","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1126/science.adp1848","finding":"\"Open foundation models can benefit society by promoting competition, accelerating innovation, and distributing power,\" but regulation risks an uneven impact on open vs. closed models.","aiGenerated":true,"topicCodes":["open_weight_release"],"origin":"promoted"},{"id":"lit-k-j-kevin-feng-nick-ritchie-pia-blumenthal-andy-parson","title":"Examining the Impact of Provenance-Enabled Media on Trust and Accuracy Perceptions","authorsOrOrg":"K. J. Kevin Feng, Nick Ritchie, Pia Blumenthal, Andy Parsons, Amy X. Zhang","year":2023,"venue":"PACM HCI (CSCW)","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3610061","finding":"Online experiment (n=595) found 'provenance information often lowered trust and caused users to doubt deceptive media,' though it could similarly reduce trust in truthful media.","aiGenerated":true,"topicCodes":["synthetic_content_provenance"],"origin":"promoted"},{"id":"lit-hanlin-zhang-benjamin-l-edelman-danilo-francati-daniel","title":"Watermarks in the Sand: Impossibility of Strong Watermarking for Generative Models","authorsOrOrg":"Hanlin Zhang, Benjamin L. Edelman, Danilo Francati, Daniele Venturi, Giuseppe Ateniese, Boaz Barak","year":2023,"venue":"arXiv (ICML 2024)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2311.04378","finding":"Proves 'under well-specified and natural assumptions, strong watermarking is impossible to achieve,' bounding what watermark mandates for generative-AI content can guarantee.","aiGenerated":true,"topicCodes":["synthetic_content_provenance"],"origin":"promoted"},{"id":"lit-vinu-sankar-sadasivan-aounon-kumar-sriram-balasubraman","title":"Can AI-Generated Text be Reliably Detected?","authorsOrOrg":"Vinu Sankar Sadasivan, Aounon Kumar, Sriram Balasubramanian, Wenxiao Wang, Soheil Feizi","year":2023,"venue":"Transactions on Machine Learning Research","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2303.11156","finding":"Shows AI-text detectors including watermarking are attackable: a 'recursive paraphrasing method can significantly reduce detection rates' while only slightly degrading text quality.","aiGenerated":true,"topicCodes":["synthetic_content_provenance"],"origin":"promoted"},{"id":"lit-alistair-knott-dino-pedreschi-raja-chatila-et-al-incl","title":"Generative AI models should include detection mechanisms as a condition for public release","authorsOrOrg":"Alistair Knott, Dino Pedreschi, Raja Chatila, et al. (incl. Stuart Russell, Yoshua Bengio)","year":2023,"venue":"Ethics and Information Technology","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s10676-023-09728-4","finding":"Argues legislation should require foundation-model developers to 'demonstrate a reliable detection mechanism for the content it generates, as a condition of its public release.'","aiGenerated":true,"topicCodes":["synthetic_content_provenance"],"origin":"promoted"},{"id":"lit-emma-strubell-ananya-ganesh-andrew-mccallum-energy-and","title":"Energy and Policy Considerations for Deep Learning in NLP","authorsOrOrg":"Emma Strubell, Ananya Ganesh, Andrew McCallum","year":2019,"venue":"ACL 2019","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.18653/v1/P19-1355","finding":"Canonical policy paper 'quantifying the approximate financial and environmental costs of training' NLP models, with 'actionable recommendations to reduce costs and improve equity.'","aiGenerated":true,"topicCodes":["environmental_impact_of_training"],"origin":"promoted"},{"id":"lit-david-patterson-joseph-gonzalez-urs-h-lzle-quoc-le-che","title":"The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink","authorsOrOrg":"David Patterson, Joseph Gonzalez, Urs Hölzle, Quoc Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David R. So, Maud Texier, Jeff Dean","year":2022,"venue":"Computer (IEEE)","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1109/MC.2022.3148714","finding":"'Four best practices can reduce ML training energy by up to 100x and CO2 emissions up to 1000x'; predicts training's total carbon footprint will plateau, then shrink.","aiGenerated":true,"topicCodes":["environmental_impact_of_training"],"origin":"promoted"},{"id":"lit-lynn-h-kaack-priya-l-donti-emma-strubell-george-kamiya","title":"Aligning artificial intelligence with climate change mitigation","authorsOrOrg":"Lynn H. Kaack, Priya L. Donti, Emma Strubell, George Kamiya, Felix Creutzig, David Rolnick","year":2022,"venue":"Nature Climate Change","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1038/s41558-022-01377-7","finding":"Presents 'a systematic framework for describing the effects of machine learning (ML) on GHG emissions' and suggests 'policy levers' for shaping ML's climate impacts.","aiGenerated":true,"topicCodes":["environmental_impact_of_training"],"origin":"promoted"},{"id":"lit-alexandra-sasha-luccioni-yacine-jernite-emma-strubell","title":"Power Hungry Processing: Watts Driving the Cost of AI Deployment?","authorsOrOrg":"Alexandra Sasha Luccioni, Yacine Jernite, Emma Strubell","year":2024,"venue":"ACM FAccT","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3630106.3658542","finding":"Measures deployment energy/carbon per 1,000 inferences, finding 'multi-purpose, generative architectures are orders of magnitude more expensive than task-specific systems.'","aiGenerated":true,"topicCodes":["environmental_impact_of_training"],"origin":"promoted"},{"id":"lit-megha-shrivastava-and-amrita-jash-china-s-semiconducto","title":"China's semiconductor conundrum: understanding US export controls and their efficacy","authorsOrOrg":"Megha Shrivastava and Amrita Jash","year":2025,"venue":"Cogent Social Sciences","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1080/23311886.2025.2528450","finding":"Argues \"America's chokepoint strategy is increasingly proving to be a fallacy\": Chinese chipmakers have \"managed to circumvent these measures\" in four ways, accelerating domestic innovation.","aiGenerated":true,"topicCodes":["compute_export_controls"],"origin":"promoted"},{"id":"lit-gregory-c-allen-center-for-strategic-and-international","title":"Choking Off China's Access to the Future of AI","authorsOrOrg":"Gregory C. Allen (Center for Strategic and International Studies)","year":2022,"venue":"CSIS","evidenceType":"think_tank","evidenceTypeLabel":"Think tank","url":"https://www.csis.org/analysis/choking-chinas-access-future-ai","finding":"Analyzes the Oct 2022 controls as \"weaponizing its dominant chokepoint positions in the global semiconductor value chain\" to block China's access to AI chips, design software, and equipment.","aiGenerated":true,"topicCodes":["compute_export_controls"],"origin":"promoted"},{"id":"lit-erich-grunewald-institute-for-ai-policy-and-strategy-a","title":"AI Chip Smuggling into China: Potential Paths, Quantities, and Countermeasures","authorsOrOrg":"Erich Grunewald (Institute for AI Policy and Strategy)","year":2023,"venue":"IAPS","evidenceType":"research_institute","evidenceTypeLabel":"Research institute","url":"https://www.iaps.ai/research/ai-chip-smuggling-into-china","finding":"Finds AI chip smuggling into China \"is already happening to a limited extent and may involve greater quantities in the future,\" proposing six countermeasures including a BIS chip registry.","aiGenerated":true,"topicCodes":["compute_export_controls"],"origin":"promoted"},{"id":"lit-david-fern-ndez-llorca-emilia-g-mez-ignacio-s-nchez-ga","title":"An interdisciplinary account of the terminological choices by EU policymakers ahead of the final agreement on the AI Act: AI system, general purpose AI system, foundation model, and generative AI","authorsOrOrg":"David Fernández-Llorca, Emilia Gómez, Ignacio Sánchez, Gabriele Mazzini","year":2025,"venue":"Artificial Intelligence and Law","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s10506-024-09412-y","finding":"Traces how the AI Act's legal text shifted across versions among the terms 'AI system, general purpose AI system, foundation model, and generative AI', exposing definitional instability in the regime.","aiGenerated":true,"topicCodes":["foundation_models"],"origin":"promoted"},{"id":"lit-martina-hulok-the-eu-model-of-ai-governance-regulating","title":"The EU model of AI governance: regulating artificial intelligence through law and policy","authorsOrOrg":"Martina Hulok","year":2025,"venue":"ERA Forum","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s12027-025-00869-1","finding":"Analyses how the AI Act's risk-based model handles general-purpose and foundation models whose 'autonomous content generation challenges legal categories of authorship, accountability, and control'.","aiGenerated":true,"topicCodes":["foundation_models"],"origin":"promoted"},{"id":"lit-jared-kaplan-sam-mccandlish-tom-henighan-tom-b-brown-b","title":"Scaling Laws for Neural Language Models","authorsOrOrg":"Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B. Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, Dario Amodei","year":2020,"venue":"arXiv (cs.LG)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2001.08361","finding":"Establishes that model 'loss scales as a power-law with model size, dataset size, and the amount of compute', the empirical basis for compute-threshold regulation of foundation models.","aiGenerated":true,"topicCodes":["foundation_models"],"origin":"promoted"},{"id":"lit-jason-wei-yi-tay-rishi-bommasani-colin-raffel-barret-z","title":"Emergent Abilities of Large Language Models","authorsOrOrg":"Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, et al.","year":2022,"venue":"arXiv (cs.CL) / TMLR","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2206.07682","finding":"Documents 'emergent abilities' that appear only above a scale threshold and 'would not have been directly predicted by extrapolating' smaller models — a core governance unpredictability problem.","aiGenerated":true,"topicCodes":["foundation_models"],"origin":"promoted"},{"id":"lit-jordan-hoffmann-sebastian-borgeaud-arthur-mensch-et-al","title":"Training Compute-Optimal Large Language Models","authorsOrOrg":"Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, et al. (DeepMind)","year":2022,"venue":"arXiv (cs.CL); NeurIPS 2022","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2203.15556","finding":"The 'Chinchilla' study shows 'model size and the number of training tokens should be scaled equally', complicating compute-only regulatory thresholds.","aiGenerated":true,"topicCodes":["foundation_models"],"origin":"promoted"},{"id":"lit-toby-shevlane-structured-access-an-emerging-paradigm-f","title":"Structured access: an emerging paradigm for safe AI deployment","authorsOrOrg":"Toby Shevlane","year":2022,"venue":"arXiv (cs.CY); The Oxford Handbook of AI Governance","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2201.05159","finding":"Proposes controlled, cloud-mediated 'structured access' to 'prevent dangerous AI capabilities from being widely accessible, whilst preserving access to AI capabilities that can be used safely'.","aiGenerated":true,"topicCodes":["foundation_models"],"origin":"promoted"},{"id":"lit-martin-kretschmer-tobias-kretschmer-alexander-peukert","title":"The risks of risk-based AI regulation: taking liability seriously","authorsOrOrg":"Martin Kretschmer, Tobias Kretschmer, Alexander Peukert, Christian Peukert","year":2023,"venue":"arXiv (cs.CY)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2311.14684","finding":"Argues the AI Act's ex-ante risk tiers under-govern foundation models and that 'taking liability seriously as the key regulatory mechanism' is a more effective lever.","aiGenerated":true,"topicCodes":["foundation_models"],"origin":"promoted"},{"id":"lit-hannah-ruschemeier-generative-ai-and-data-protection","title":"Generative AI and data protection","authorsOrOrg":"Hannah Ruschemeier","year":2025,"venue":"Cambridge Forum on AI: Law and Governance","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1017/cfl.2024.2","finding":"Examines friction between foundation-model training and the GDPR, noting models that 'memorize and leak pieces of training data' cannot be treated as anonymous.","aiGenerated":true,"topicCodes":["foundation_models"],"origin":"promoted"},{"id":"lit-mary-phuong-matthew-aitchison-elliot-catt-et-al-google","title":"Evaluating Frontier Models for Dangerous Capabilities","authorsOrOrg":"Mary Phuong, Matthew Aitchison, Elliot Catt, et al. (Google DeepMind)","year":2024,"venue":"arXiv (cs.LG)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2403.13793","finding":"Pilots dangerous-capability evaluations (persuasion, cyber, self-proliferation) on frontier models, finding 'early warning signs' but no strong present danger — grounding evaluation-based gating.","aiGenerated":true,"topicCodes":["foundation_models"],"origin":"promoted"},{"id":"lit-jai-vipra-anton-korinek-market-concentration-implicati","title":"Market Concentration Implications of Foundation Models","authorsOrOrg":"Jai Vipra, Anton Korinek","year":2023,"venue":"arXiv (econ.GN); Brookings","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2311.01550","finding":"Argues foundation models tend toward 'natural monopoly' and that regulators must ensure 'the contestability of the market by tackling strategic behavior'.","aiGenerated":true,"topicCodes":["foundation_models"],"origin":"promoted"},{"id":"lit-janet-egan-lennart-heim-oversight-for-frontier-ai-thro","title":"Oversight for Frontier AI through a Know-Your-Customer Scheme for Compute Providers","authorsOrOrg":"Janet Egan, Lennart Heim","year":2023,"venue":"arXiv (cs.CY); GovAI","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2310.13625","finding":"Proposes a banking-style KYC regime for cloud compute providers because 'compute is emerging as a node for oversight', enabling record-keeping and reporting of high-risk training.","aiGenerated":true,"topicCodes":["compute_reporting"],"origin":"promoted"},{"id":"lit-lennart-heim-tim-fist-janet-egan-sihao-huang-stephen-z","title":"Governing Through the Cloud: The Intermediary Role of Compute Providers in AI Regulation","authorsOrOrg":"Lennart Heim, Tim Fist, Janet Egan, Sihao Huang, Stephen Zekany, Robert Trager, Michael A. Osborne, Noa Zilberman","year":2024,"venue":"arXiv (cs.CY)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2403.08501","finding":"Argues 'compute providers should have legal obligations' to secure infrastructure, keep records, verify activity and report frontier training as regulatory intermediaries.","aiGenerated":true,"topicCodes":["compute_reporting"],"origin":"promoted"},{"id":"lit-akash-r-wasil-tom-reed-jack-william-miller-peter-barne","title":"Verification methods for international AI agreements","authorsOrOrg":"Akash R. Wasil, Tom Reed, Jack William Miller, Peter Barnett","year":2024,"venue":"arXiv (cs.CY)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2408.16074","finding":"Surveys '10 verification methods that could detect... unauthorized AI training... and unauthorized data centers', mapping the technical basis for compute-disclosure regimes.","aiGenerated":true,"topicCodes":["compute_reporting","catastrophic_risk"],"origin":"promoted"},{"id":"lit-anka-reuel-ben-bucknall-stephen-casper-tim-fist-lennar","title":"Open Problems in Technical AI Governance","authorsOrOrg":"Anka Reuel, Ben Bucknall, Stephen Casper, Tim Fist, Lennart Heim, et al. (34 authors)","year":2024,"venue":"arXiv (cs.CY)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2407.14981","finding":"Catalogs open problems in 'technical analysis and tools for supporting the effective governance of AI', including compute measurement, verification and reporting gaps.","aiGenerated":true,"topicCodes":["compute_reporting"],"origin":"promoted"},{"id":"lit-matteo-pistillo-pablo-villalobos-defending-compute-thr","title":"Defending Compute Thresholds Against Legal Loopholes","authorsOrOrg":"Matteo Pistillo, Pablo Villalobos","year":2025,"venue":"arXiv (cs.CY)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2502.00003","finding":"Identifies 'enhancement techniques that are capable of decreasing training compute usage while preserving... model capabilities', exposing loopholes in compute-reporting thresholds.","aiGenerated":true,"topicCodes":["compute_reporting"],"origin":"promoted"},{"id":"lit-james-petrie-near-term-enforcement-of-ai-chip-export-c","title":"Near-Term Enforcement of AI Chip Export Controls Using a Firmware-Based Design for Offline Licensing","authorsOrOrg":"James Petrie","year":2024,"venue":"arXiv (cs.CR)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2404.18308","finding":"Proposes firmware 'disabling AI chips unless they have an unused license from a regulator', a hardware-enforceable mechanism for export-control compliance on chips like the H100.","aiGenerated":true,"topicCodes":["compute_export_controls"],"origin":"promoted"},{"id":"lit-chan-yuan-wong-henry-wai-chung-yeung-shaopeng-huang-ja","title":"Geopolitics and the changing landscape of global value chains and competition in the global semiconductor industry: Rivalry and catch-up in chip manufacturing in East Asia","authorsOrOrg":"Chan-Yuan Wong, Henry Wai-chung Yeung, Shaopeng Huang, Jaeyong Song, Keun Lee","year":2024,"venue":"Technological Forecasting and Social Change","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1016/j.techfore.2024.123749","finding":"Analyses how geopolitics reshapes semiconductor global value chains and East-Asian rivalry/catch-up, the structural backdrop against which chip export controls operate.","aiGenerated":true,"topicCodes":["compute_export_controls"],"origin":"promoted"},{"id":"lit-do-joon-park-shuzhi-liu-a-study-on-the-economic-effect","title":"A Study on the Economic Effects of U.S. Export Controls on Semiconductors to China","authorsOrOrg":"Do-Joon Park, Shuzhi Liu","year":2023,"venue":"International Commerce and Information Review (Korea Interna","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.16980/jitc.19.1.202302.129","finding":"Empirically estimates the economic effects of US semiconductor export controls on China, a non-Western quantitative assessment of control efficacy.","aiGenerated":true,"topicCodes":["compute_export_controls"],"origin":"promoted"},{"id":"lit-henry-farrell-abraham-l-newman-weaponized-interdepende","title":"Weaponized Interdependence: How Global Economic Networks Shape State Coercion","authorsOrOrg":"Henry Farrell, Abraham L. Newman","year":2019,"venue":"International Security","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1162/isec_a_00351","finding":"The 'chokepoint' and 'panopticon' theory of how states exploit central network hubs for coercion — the IR foundation for using concentrated chip supply chains as export-control leverage.","aiGenerated":true,"topicCodes":["compute_export_controls"],"origin":"promoted"},{"id":"lit-xueyue-liu-yu-liu-alexey-makarin-jaya-wen-export-contr","title":"Export Controls and Innovation in Sanctioned Countries","authorsOrOrg":"Xueyue Liu, Yu Liu, Alexey Makarin, Jaya Wen","year":2025,"venue":"Harvard Business School Working Paper 25-004","evidenceType":"working_paper","evidenceTypeLabel":"Working paper","url":"https://www.hbs.edu/faculty/Pages/item.aspx?num=66221","finding":"Using the 2007 US 'China Rule', finds sanctioned Chinese firms raised R&D by ~49% and patenting by ~41% — evidence export controls can accelerate the target's indigenous innovation.","aiGenerated":true,"topicCodes":["compute_export_controls"],"origin":"promoted"},{"id":"lit-pedro-robles-daniel-j-mallinson-eric-best-cheryl-devan","title":"Global perspectives on regulating facial recognition technology utilization for criminal justice arrests","authorsOrOrg":"Pedro Robles, Daniel J. Mallinson, Eric Best, Cheryl Devaney, Lauren Azevedo","year":2025,"venue":"Global Public Policy and Governance","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s43508-025-00117-9","finding":"Comparative study of facial-recognition regulation for arrests across democracies finds frameworks are inconsistent and unclear, raising privacy and civil-liberties risks.","aiGenerated":true,"topicCodes":["biometric_id"],"origin":"promoted"},{"id":"lit-nessa-lynch-facial-recognition-technology-in-policing","title":"Facial Recognition Technology in Policing and Security—Case Studies in Regulation","authorsOrOrg":"Nessa Lynch","year":2024,"venue":"Laws","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.3390/laws13030035","finding":"Through regulatory case studies, argues facial recognition in policing requires a tailored governance framework grounded in necessity and proportionality rather than ad hoc deployment.","aiGenerated":true,"topicCodes":["biometric_id","national_security_carveouts"],"origin":"promoted"},{"id":"lit-dallas-hill-christopher-d-o-connor-andrea-slane-police","title":"Police use of facial recognition technology: The potential for engaging the public through co-constructed policy-making","authorsOrOrg":"Dallas Hill, Christopher D. O'Connor, Andrea Slane","year":2022,"venue":"International Journal of Police Science & Management","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1177/14613557221089558","finding":"Argues meaningful public participation and an oversight framework should govern police adoption of FRT, presenting co-constructed policymaking as a model for addressing surveillance concerns.","aiGenerated":true,"topicCodes":["biometric_id"],"origin":"promoted"},{"id":"lit-emelie-stiernstr-mer-facial-recognition-technology-in","title":"Facial recognition technology in law enforcement: a scoping review of existing empirical studies","authorsOrOrg":"Emelie Stiernströmer","year":2026,"venue":"Police Practice and Research","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1080/15614263.2026.2627208","finding":"Scoping review mapping the empirical evidence base on law-enforcement FRT, identifying gaps in research on real-world identification use and its governance.","aiGenerated":true,"topicCodes":["biometric_id"],"origin":"promoted"},{"id":"lit-mais-qandeel-facial-recognition-technology-regulations","title":"Facial recognition technology: regulations, rights and the rule of law","authorsOrOrg":"Mais Qandeel","year":2024,"venue":"Frontiers in Big Data","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.3389/fdata.2024.1354659","finding":"Argues states have an \"international obligation...to domestically regulate\" facial recognition as an unacceptable-risk AI system to protect human rights and the rule of law.","aiGenerated":true,"topicCodes":["biometric_id"],"origin":"promoted"},{"id":"lit-ursula-rao-vijayanka-nair-aadhaar-governing-with-biome","title":"Aadhaar: Governing with Biometrics","authorsOrOrg":"Ursula Rao, Vijayanka Nair","year":2019,"venue":"South Asia: Journal of South Asian Studies","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1080/00856401.2019.1595343","finding":"Analyses India's Aadhaar as a biometric mode of governance that links bodies to databases, producing new regimes of welfare inclusion and exclusion.","aiGenerated":true,"topicCodes":["biometric_id"],"origin":"promoted"},{"id":"lit-bernard-keenan-automatic-facial-recognition-and-the-in","title":"Automatic Facial Recognition and the Intensification of Police Surveillance","authorsOrOrg":"Bernard Keenan","year":2021,"venue":"The Modern Law Review","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1111/1468-2230.12623","finding":"Analysing Bridges v South Wales Police, shows live AFR was ruled unlawful on Article 8 privacy, data-protection-impact-assessment, and public-sector-equality-duty grounds.","aiGenerated":true,"topicCodes":["biometric_id"],"origin":"promoted"},{"id":"lit-daragh-murray-police-use-of-retrospective-facial-recog","title":"Police Use of Retrospective Facial Recognition Technology: A Step Change in Surveillance Capability Necessitating an Evolution of the Human Rights Law Framework","authorsOrOrg":"Daragh Murray","year":2024,"venue":"The Modern Law Review","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1111/1468-2230.12862","finding":"Argues retrospective facial recognition is a step change in police surveillance whose chilling effects and weak legal basis demand an evolved human-rights framework.","aiGenerated":true,"topicCodes":["biometric_id"],"origin":"promoted"},{"id":"lit-g-o-mohler-m-b-short-sean-malinowski-mark-johnson-g-e","title":"Randomized Controlled Field Trials of Predictive Policing","authorsOrOrg":"G. O. Mohler, M. B. Short, Sean Malinowski, Mark Johnson, G. E. Tita, Andrea L. Bertozzi, P. J. Brantingham","year":2015,"venue":"Journal of the American Statistical Association","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1080/01621459.2015.1077710","finding":"First RCT field trials of predictive policing report algorithmic hotspot predictions led to crime reductions versus analyst-designated patrols.","aiGenerated":true,"topicCodes":["criminal_justice"],"origin":"promoted"},{"id":"lit-youngsub-lee-ben-bradford-krisztian-posch-the-effectiv","title":"The Effectiveness of Big Data-Driven Predictive Policing: Systematic Review","authorsOrOrg":"Youngsub Lee, Ben Bradford, Krisztian Posch","year":2024,"venue":"Justice Evaluation Journal","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1080/24751979.2024.2371781","finding":"Systematic review of 161 articles finds claimed effectiveness underpins legitimacy of predictive policing in the UK and US while algorithmic bias and data-concentration concerns persist.","aiGenerated":true,"topicCodes":["criminal_justice"],"origin":"promoted"},{"id":"lit-shai-farber-machines-of-justice-a-systematic-review-of","title":"Machines of justice: A systematic review of AI applications in policing and criminal justice","authorsOrOrg":"Shai Farber","year":2026,"venue":"The Police Journal: Theory, Practice and Principles","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1177/0032258X261439572","finding":"Synthesises a decade of AI-in-criminal-justice research, flagging \"algorithmic bias, opacity, and due process\" and recommending safeguards for equity and accountability.","aiGenerated":true,"topicCodes":["criminal_justice"],"origin":"promoted"},{"id":"lit-danielle-ensign-sorelle-a-friedler-scott-neville-carlo","title":"Runaway Feedback Loops in Predictive Policing","authorsOrOrg":"Danielle Ensign, Sorelle A. Friedler, Scott Neville, Carlos Scheidegger, Suresh Venkatasubramanian","year":2018,"venue":"Proceedings of the 1st Conference on Fairness, Accountabilit","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://proceedings.mlr.press/v81/ensign18a.html","finding":"Proves mathematically that learning from discovered-crime data sends police repeatedly to the same neighbourhoods \"regardless of the true crime rate,\" and shows how to correct it.","aiGenerated":true,"topicCodes":["criminal_justice"],"origin":"promoted"},{"id":"lit-andrew-d-selbst-disparate-impact-in-big-data-policing","title":"Disparate Impact in Big Data Policing","authorsOrOrg":"Andrew D. Selbst","year":2017,"venue":"Georgia Law Review (","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://georgialawreview.org/wp-content/uploads/2025/01/Andrew-D.-Selbst-Disparate-Impact-in-Big-Data-Policing-52-Georgia-Law-Review-2018.pdf","finding":"Argues data-driven predictive policing can produce disparate racial impacts even when well-intentioned, and proposes algorithmic impact statements as a legal remedy.","aiGenerated":true,"topicCodes":["criminal_justice"],"origin":"promoted"},{"id":"lit-miri-zilka-holli-sargeant-adrian-weller-transparency-g","title":"Transparency, Governance and Regulation of Algorithmic Tools Deployed in the Criminal Justice System: a UK Case Study","authorsOrOrg":"Miri Zilka, Holli Sargeant, Adrian Weller","year":2022,"venue":"Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, a","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3514094.3534200","finding":"UK case study maps algorithmic tools used across the criminal-justice system and finds fragmented governance and weak transparency over their deployment.","aiGenerated":true,"topicCodes":["criminal_justice"],"origin":"promoted"},{"id":"lit-megan-t-stevenson-assessing-risk-assessment-in-action","title":"Assessing Risk Assessment in Action","authorsOrOrg":"Megan T. Stevenson","year":2018,"venue":"Minnesota Law Review (","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://www.minnesotalawreview.org/wp-content/uploads/2019/01/13Stevenson_MLR.pdf","finding":"Empirical study of Kentucky's mandatory pretrial risk assessment finds an initial small detention drop that dissipated as judges reverted, with limited net change and modest disparity effects.","aiGenerated":true,"topicCodes":["criminal_justice"],"origin":"promoted"},{"id":"lit-henrik-palmer-olsen-thomas-troels-hildebrandt-corneliu","title":"The Right to Transparency in Public Governance: Freedom of Information and the Use of Artificial Intelligence by Public Agencies","authorsOrOrg":"Henrik Palmer Olsen, Thomas Troels Hildebrandt, Cornelius Wiesener, Matthias Smed Larsen, Asbjørn William Ammitzbøll Flügge","year":2024,"venue":"Digital Government: Research and Practice","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3632753","finding":"Finds freedom-of-information regimes \"generally only grant access to existing documents\" and that with \"no mature standard for documenting AI models,\" public-sector AI transparency is limited.","aiGenerated":true,"topicCodes":["transparency"],"origin":"promoted"},{"id":"lit-margot-e-kaminski-gianclaudio-malgieri-algorithmic-imp","title":"Algorithmic impact assessments under the GDPR: producing multi-layered explanations","authorsOrOrg":"Margot E. Kaminski, Gianclaudio Malgieri","year":2020,"venue":"International Data Privacy Law","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1093/idpl/ipaa020","finding":"Proposes that GDPR algorithmic impact assessments be combined with individual rights to produce layered, system-and-individual explanations of automated decisions.","aiGenerated":true,"topicCodes":["transparency"],"origin":"promoted"},{"id":"lit-jacob-metcalf-emanuel-moss-elizabeth-anne-watkins-ranj","title":"Algorithmic Impact Assessments and Accountability: The Co-construction of Impacts","authorsOrOrg":"Jacob Metcalf, Emanuel Moss, Elizabeth Anne Watkins, Ranjit Singh, Madeleine Clare Elish","year":2021,"venue":"Proceedings of the 2021 ACM Conference on Fairness, Accounta","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3442188.3445935","finding":"Argues algorithmic impact assessments depend on how \"impacts\" are co-constructed, and that AIA regimes must define who measures impacts and to whom accountability is owed.","aiGenerated":true,"topicCodes":["transparency"],"origin":"promoted"},{"id":"lit-corinne-cath-fieke-jansen-dutch-comfort-the-limits-of","title":"Dutch Comfort: The Limits of AI Governance through Municipal Registers","authorsOrOrg":"Corinne Cath, Fieke Jansen","year":2022,"venue":"Techné: Research in Philosophy and Technology","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.5840/techne202323172","finding":"Critiques Amsterdam/Helsinki AI registers as risking \"ethics theater\" by decontextualising and depoliticising algorithmic systems used in the digital welfare state.","aiGenerated":true,"topicCodes":["transparency"],"origin":"promoted"},{"id":"lit-ulla-maija-mylly-transparent-ai-navigating-between-rul","title":"Transparent AI? Navigating Between Rules on Trade Secrets and Access to Information","authorsOrOrg":"Ulla-Maija Mylly","year":2023,"venue":"IIC - International Review of Intellectual Property and Comp","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s40319-023-01328-5","finding":"Examines the tension between AI Act disclosure duties and trade-secret protection, identifying which technical details lack trade-secret eligibility to enable transparency.","aiGenerated":true,"topicCodes":["transparency"],"origin":"promoted"},{"id":"lit-sarah-sterz-kevin-baum-sebastian-biewer-holger-hermann","title":"On the Quest for Effectiveness in Human Oversight: Interdisciplinary Perspectives","authorsOrOrg":"Sarah Sterz, Kevin Baum, Sebastian Biewer, Holger Hermanns, Anne Lauber-Rönsberg, Philip Meinel, Markus Langer","year":2024,"venue":"Proceedings of the 2024 ACM Conference on Fairness, Accounta","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3630106.3659051","finding":"Synthesises interdisciplinary evidence to argue that legally mandated human oversight of AI is often ineffective ('rubber-stamp') unless effectiveness conditions are explicitly designed for.","aiGenerated":true,"topicCodes":["transparency"],"origin":"promoted"},{"id":"lit-petros-terzis-michael-veale-no-lle-gaumann-law-and-the","title":"Law and the Emerging Political Economy of Algorithmic Audits","authorsOrOrg":"Petros Terzis, Michael Veale, Noëlle Gaumann","year":2024,"venue":"Proceedings of the 2024 ACM Conference on Fairness, Accounta","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3630106.3658970","finding":"Analyses how AI-audit mandates create a new political economy of auditing, warning that audit markets can entrench rather than constrain power without underlying governance.","aiGenerated":true,"topicCodes":["transparency"],"origin":"promoted"},{"id":"lit-beatriz-kira-when-non-consensual-intimate-deepfakes-go","title":"When non-consensual intimate deepfakes go viral: The insufficiency of the UK Online Safety Act","authorsOrOrg":"Beatriz Kira","year":2024,"venue":"Computer Law & Security Review","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1016/j.clsr.2024.106024","finding":"Argues the UK Online Safety Act 2023 inadequately addresses non-consensual intimate deepfakes as image-based sexual abuse, leaving enforcement and takedown gaps.","aiGenerated":true,"topicCodes":["deepfakes"],"origin":"promoted"},{"id":"lit-valentine-ugwuoke-and-madelyn-rose-sanfilippo-the-curr","title":"The Current Landscape of Deepfake Legislation in the United States","authorsOrOrg":"Valentine Ugwuoke and Madelyn Rose Sanfilippo","year":2025,"venue":"Journal of Information Policy","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.5325/jinfopoli.15.2025.0004","finding":"Thematic analysis of 319 state deepfake bills (2019-2024) finds a fragmented patchwork concentrated on political and sexually-explicit content.","aiGenerated":true,"topicCodes":["deepfakes"],"origin":"promoted"},{"id":"lit-joshua-habgood-coote-deepfakes-and-the-epistemic-apoca","title":"Deepfakes and the epistemic apocalypse","authorsOrOrg":"Joshua Habgood-Coote","year":2023,"venue":"Synthese","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s11229-023-04097-3","finding":"Argues deepfake threat to recordings is overstated once social norms are recognised and that policy has been overly focused on technological interventions.","aiGenerated":true,"topicCodes":["deepfakes"],"origin":"promoted"},{"id":"lit-keith-raymond-harris-ai-or-your-lying-eyes-some-shortc","title":"AI or Your Lying Eyes: Some Shortcomings of Artificially Intelligent Deepfake Detectors","authorsOrOrg":"Keith Raymond Harris","year":2024,"venue":"Philosophy & Technology","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s13347-024-00700-8","finding":"Argues detector-based solutions depend on scarce institutional trust and risk undermining epistemic autonomy, so purely technological fixes for deepfakes are dim.","aiGenerated":true,"topicCodes":["deepfakes"],"origin":"promoted"},{"id":"lit-kaylyn-jackson-schiff-daniel-s-schiff-and-nat-lia-s-bu","title":"The Liar's Dividend: Can Politicians Claim Misinformation to Evade Accountability?","authorsOrOrg":"Kaylyn Jackson Schiff, Daniel S. Schiff, and Natália S. Bueno","year":2024,"venue":"American Political Science Review","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1017/S0003055423001454","finding":"Five survey experiments (>15,000 US adults) show false 'it's a deepfake/fake news' claims can help politicians retain support, evidencing the liar's dividend.","aiGenerated":true,"topicCodes":["deepfakes"],"origin":"promoted"},{"id":"lit-huijuan-peng-and-pey-woan-lee-reimagining-u-s-tort-law","title":"Reimagining U.S. Tort Law for Deepfake Harms: Comparative Insights from China and Singapore","authorsOrOrg":"Huijuan Peng and Pey-Woan Lee","year":2025,"venue":"Journal of Tort Law","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1515/jtl-2025-0028","finding":"Argues fragmented US tort doctrines (defamation, publicity, IIED) are ill-suited to deepfake harms and draws remedial lessons from Chinese and Singaporean law.","aiGenerated":true,"topicCodes":["deepfakes"],"origin":"promoted"},{"id":"lit-mateusz-abuz-deep-fakes-and-the-artificial-intelligenc","title":"Deep fakes and the Artificial Intelligence Act—An important signal or a missed opportunity?","authorsOrOrg":"Mateusz Łabuz","year":2024,"venue":"Policy & Internet","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1002/poi3.406","finding":"Critiques the EU AI Act's placement of deepfakes in the 'limited risk' tier, leaving transparency obligations as the only direct safeguard without bans or victim remedies.","aiGenerated":true,"topicCodes":["deepfakes"],"origin":"promoted"},{"id":"lit-mateusz-abuz-a-teleological-interpretation-of-the-defi","title":"A Teleological Interpretation of the Definition of DeepFakes in the EU Artificial Intelligence Act—A Purpose-Based Approach to Potential Problems With the Word 'Existing'","authorsOrOrg":"Mateusz Łabuz","year":2025,"venue":"Policy & Internet","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1002/poi3.435","finding":"Warns a narrow reading of 'existing' in the AI Act's deepfake definition could exclude synthetic media from transparency duties, urging a teleological interpretation.","aiGenerated":true,"topicCodes":["deepfakes"],"origin":"promoted"},{"id":"lit-bao-kham-chau-and-george-he-audio-deepfakes-and-the-re","title":"Audio deepfakes and the regulation of the landlords of creativity","authorsOrOrg":"Bao Kham Chau and George He","year":2025,"venue":"Cambridge Forum on AI: Law and Governance","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1017/cfl.2025.10011","finding":"Argues US, EU and Chinese regimes fail to assign audio-deepfake liability to 'landlords of creativity' (foundation-model providers) and proposes holding them accountable.","aiGenerated":true,"topicCodes":["deepfakes"],"origin":"promoted"},{"id":"lit-rebecca-umbach-nicola-henry-gemma-faye-beard-and-colle","title":"Non-Consensual Synthetic Intimate Imagery: Prevalence, Attitudes, and Knowledge in 10 Countries","authorsOrOrg":"Rebecca Umbach, Nicola Henry, Gemma Faye Beard, and Colleen M. Berryessa","year":2024,"venue":"CHI '24: Proceedings of the CHI Conference on Human Factors ","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3613904.3642382","finding":"Survey of >16,000 respondents across 10 countries finds NSII victimization/perpetration persists even where specific laws exist, suggesting current laws under-deter.","aiGenerated":true,"topicCodes":["deepfakes"],"origin":"promoted"},{"id":"lit-xuandong-zhao-sam-gunn-miranda-christ-nicholas-carlini","title":"SoK: Watermarking for AI-Generated Content","authorsOrOrg":"Xuandong Zhao, Sam Gunn, Miranda Christ, Nicholas Carlini, Florian Tramèr, Dawn Song, et al.","year":2024,"venue":"IEEE Symposium on Security and Privacy (S&P) 2025 (accepted)","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.48550/arXiv.2411.18479","finding":"Systematizes watermarking for AI content, formalizing robustness/security goals and limits that directly ground regulatory provenance and labeling mandates.","aiGenerated":true,"topicCodes":["synthetic_content_provenance"],"origin":"promoted"},{"id":"lit-bram-rijsbosch-gijs-van-dijck-and-konrad-kollnig-missi","title":"Missing the Mark: Adoption of Watermarking for Generative AI Systems in Practice and Implications Under the New EU AI Act","authorsOrOrg":"Bram Rijsbosch, Gijs van Dijck, and Konrad Kollnig","year":2026,"venue":"Policy & Internet","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1002/poi3.70041","finding":"Empirical audit finds only 38% of AI image generators implement adequate watermarking and 18% deepfake labelling, exposing a compliance gap under EU AI Act Article 50.","aiGenerated":true,"topicCodes":["synthetic_content_provenance"],"origin":"promoted"},{"id":"lit-mimi-zou-and-lu-zhang-navigating-china-s-regulatory-ap","title":"Navigating China's regulatory approach to generative artificial intelligence and large language models","authorsOrOrg":"Mimi Zou and Lu Zhang","year":2025,"venue":"Cambridge Forum on AI: Law and Governance","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1017/cfl.2024.4","finding":"Analyses China's 2022 deep-synthesis and 2023 generative-AI rules, including mandatory labelling/watermarking of synthetic content as a provenance-governance model.","aiGenerated":true,"topicCodes":["synthetic_content_provenance"],"origin":"promoted"},{"id":"lit-kyrie-zhixuan-zhou-abhinav-choudhry-ece-gumusel-and-ma","title":"'Sora is incredible and scary': public perceptions and governance challenges of text-to-video generative AI models","authorsOrOrg":"Kyrie Zhixuan Zhou, Abhinav Choudhry, Ece Gumusel, and Madelyn Rose Sanfilippo","year":2025,"venue":"Information Research (iConference 2025 proceedings)","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.47989/ir30iconf47290","finding":"Qualitative analysis of public commentary on Sora finds blurred real/fake boundaries drive demand for law-enforced AI-content labelling and provenance.","aiGenerated":true,"topicCodes":["synthetic_content_provenance"],"origin":"promoted"},{"id":"lit-claire-r-leibowicz-and-christian-h-cardona-partnership","title":"From Principles to Practices: Lessons Learned from Applying Partnership on AI's (PAI) Synthetic Media Framework to 11 Use Cases","authorsOrOrg":"Claire R. Leibowicz and Christian H. Cardona (Partnership on AI)","year":2024,"venue":"arXiv:2407.13025 (preprint)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://doi.org/10.48550/arXiv.2407.13025","finding":"Applies PAI's Synthetic Media Framework to 11 real cases, finding disclosure/provenance recommendations could have mitigated harm in several 2024-election deepfake incidents.","aiGenerated":true,"topicCodes":["synthetic_content_provenance"],"origin":"promoted"},{"id":"lit-emre-bayaml-o-lu-the-right-to-contest-automated-decisi","title":"The right to contest automated decisions under the General Data Protection Regulation: Beyond the so-called 'right to explanation'","authorsOrOrg":"Emre Bayamlıoğlu","year":2022,"venue":"Regulation & Governance","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1111/rego.12391","finding":"Recasts GDPR Art. 22's right to contest as the core due-process remedy and maps administrative, procedural and technical transparency mechanisms to implement it.","aiGenerated":true,"topicCodes":["redress"],"origin":"promoted"},{"id":"lit-rebecca-williams-rethinking-administrative-law-for-alg","title":"Rethinking Administrative Law for Algorithmic Decision Making","authorsOrOrg":"Rebecca Williams","year":2022,"venue":"Oxford Journal of Legal Studies","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1093/ojls/gqab032","finding":"Argues administrative-law principles (reasons, review, contestation) should structure remedies and procedural fairness for public-sector automated decisions.","aiGenerated":true,"topicCodes":["redress"],"origin":"promoted"},{"id":"lit-mireia-yurrita-tim-draws-agathe-balayn-dave-murray-rus","title":"Disentangling Fairness Perceptions in Algorithmic Decision-Making: the Effects of Explanations, Human Oversight, and Contestability","authorsOrOrg":"Mireia Yurrita, Tim Draws, Agathe Balayn, Dave Murray-Rust, Nava Tintarev, and Alessandro Bozzon","year":2023,"venue":"CHI '23: Proceedings of the CHI Conference on Human Factors ","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3544548.3581161","finding":"User study (N=267) finds contestability (appeal processes) drives procedural-fairness perceptions while human oversight alone shows no significant effect.","aiGenerated":true,"topicCodes":["redress"],"origin":"promoted"},{"id":"lit-naveena-karusala-sohini-upadhyay-rajesh-veeraraghavan","title":"Understanding Contestability on the Margins: Implications for the Design of Algorithmic Decision-making in Public Services","authorsOrOrg":"Naveena Karusala, Sohini Upadhyay, Rajesh Veeraraghavan, and Krzysztof Z. Gajos","year":2024,"venue":"CHI '24: Proceedings of the CHI Conference on Human Factors ","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3613904.3641898","finding":"Field study shows marginalized public-service users need intermediaries and informal channels for contestation, challenging individualistic right-to-contest designs.","aiGenerated":true,"topicCodes":["redress"],"origin":"promoted"},{"id":"lit-kars-alfrink-ianus-keller-neelke-doorn-and-gerd-kortue","title":"Contestable Camera Cars: A Speculative Design Exploration of Public AI That Is Open and Responsive to Dispute","authorsOrOrg":"Kars Alfrink, Ianus Keller, Neelke Doorn, and Gerd Kortuem","year":2023,"venue":"CHI '23: Proceedings of the CHI Conference on Human Factors ","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3544548.3580984","finding":"Speculative design of a contestable public-AI system specifies concrete redress affordances: explanations, appeal channels, an adversarial arena and a duty to respond.","aiGenerated":true,"topicCodes":["redress"],"origin":"promoted"},{"id":"lit-mireia-yurrita-himanshu-verma-agathe-balayn-kars-alfri","title":"Identifying Algorithmic Decision Subjects' Needs for Meaningful Contestability","authorsOrOrg":"Mireia Yurrita, Himanshu Verma, Agathe Balayn, Kars Alfrink, Ujwal Gadiraju, and Alessandro Bozzon","year":2025,"venue":"Proceedings of the ACM on Human-Computer Interaction (CSCW)","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3757415","finding":"Empirically elicits what decision subjects need for contestation to be 'meaningful', informing the design of effective remedies and appeal mechanisms for ADM.","aiGenerated":true,"topicCodes":["redress"],"origin":"promoted"},{"id":"lit-timoth-e-schmude-mireia-yurrita-kars-alfrink-thomas-le","title":"Two Means to an End Goal: Connecting Explainability and Contestability in the Regulation of Public Sector AI","authorsOrOrg":"Timothée Schmude, Mireia Yurrita, Kars Alfrink, Thomas Le Goff, and Tiphaine Viard","year":2025,"venue":"arXiv:2504.18236 (accepted, ACM FAccT 2025)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://doi.org/10.48550/arXiv.2504.18236","finding":"Interview study with 14 regulation experts distinguishes judicial vs non-judicial and individual vs collective contestation channels for public-sector AI remedies.","aiGenerated":true,"topicCodes":["redress"],"origin":"promoted"},{"id":"lit-daron-acemoglu-and-pascual-restrepo-automation-and-new","title":"Automation and New Tasks: How Technology Displaces and Reinstates Labor","authorsOrOrg":"Daron Acemoglu and Pascual Restrepo","year":2019,"venue":"Journal of Economic Perspectives","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1257/jep.33.2.3","finding":"Task-based framework: automation's displacement effect shifts the task content of production against labor and can reduce labor demand even as it raises productivity, counterbalanced only by new-task reinstatement.","aiGenerated":true,"topicCodes":["ai_worker_displacement"],"origin":"promoted"},{"id":"lit-daron-acemoglu-and-pascual-restrepo-tasks-automation-a","title":"Tasks, Automation, and the Rise in U.S. Wage Inequality","authorsOrOrg":"Daron Acemoglu and Pascual Restrepo","year":2022,"venue":"Econometrica","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.3982/ECTA19815","finding":"Estimates 50–70% of changes in the U.S. wage structure over four decades are accounted for by relative wage declines of worker groups specialized in routine tasks in rapidly-automating industries.","aiGenerated":true,"topicCodes":["ai_worker_displacement"],"origin":"promoted"},{"id":"lit-david-h-autor-why-are-there-still-so-many-jobs-the-his","title":"Why Are There Still So Many Jobs? The History and Future of Workplace Automation","authorsOrOrg":"David H. Autor","year":2015,"venue":"Journal of Economic Perspectives","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1257/jep.29.3.3","finding":"Argues commentators overstate machine substitution and ignore complementarities: automation substitutes for some tasks but raises demand for the labor that complements it, explaining persistent employment.","aiGenerated":true,"topicCodes":["ai_worker_displacement"],"origin":"promoted"},{"id":"lit-michael-webb-the-impact-of-artificial-intelligence-on","title":"The Impact of Artificial Intelligence on the Labor Market","authorsOrOrg":"Michael Webb","year":2019,"venue":"SSRN Working Paper","evidenceType":"working_paper","evidenceTypeLabel":"Working paper","url":"https://doi.org/10.2139/ssrn.3482150","finding":"Patent-to-task text-overlap exposure measure finds AI targets high-skilled tasks (e.g., programmers more exposed than 94% of occupations), predicting reduced 90:10 wage inequality but no effect on the top 1%.","aiGenerated":true,"topicCodes":["ai_worker_displacement"],"origin":"promoted"},{"id":"lit-daron-acemoglu-the-simple-macroeconomics-of-ai","title":"The simple macroeconomics of AI","authorsOrOrg":"Daron Acemoglu","year":2025,"venue":"Economic Policy","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1093/epolic/eiae042","finding":"Task-based model estimates AI raises TFP only ~0.66% over ten years and warns benefits may not be broadly shared, tempering claims of large near-term macroeconomic and labor effects.","aiGenerated":true,"topicCodes":["ai_worker_displacement"],"origin":"promoted"},{"id":"lit-erik-brynjolfsson-danielle-li-and-lindsey-r-raymond-ge","title":"Generative AI at Work","authorsOrOrg":"Erik Brynjolfsson, Danielle Li and Lindsey R. Raymond","year":2025,"venue":"Quarterly Journal of Economics","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1093/qje/qjae044","finding":"Staggered rollout of a GPT-based assistant to 5,172 support agents raised issues-resolved-per-hour 14% on average and 34% for novices, compressing the skill gap rather than displacing high-skill workers.","aiGenerated":true,"topicCodes":["ai_worker_displacement"],"origin":"promoted"},{"id":"lit-isabel-ebert-isabelle-wildhaber-and-jeremias-adams-pra","title":"Big Data in the workplace: Privacy Due Diligence as a human rights-based approach to employee privacy protection","authorsOrOrg":"Isabel Ebert, Isabelle Wildhaber and Jeremias Adams-Prassl","year":2021,"venue":"Big Data & Society","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1177/20539517211013051","finding":"Proposes 'privacy due diligence' as a human-rights-based regulatory approach to algorithmic management and worker monitoring, arguing data-protection law alone inadequately constrains employer surveillance.","aiGenerated":true,"topicCodes":["employment"],"origin":"promoted"},{"id":"lit-jeremias-adams-prassl-halefom-abraha-aislinn-kelly-lyt","title":"Regulating algorithmic management: A blueprint","authorsOrOrg":"Jeremias Adams-Prassl, Halefom Abraha, Aislinn Kelly-Lyth, Michael 'Six' Silberman and Sangh Rakshita","year":2023,"venue":"European Labour Law Journal","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1177/20319525231167299","finding":"Identifies regulatory gaps from algorithmic management (privacy harms, information asymmetries, loss of human agency) and sets out a concrete policy blueprint to address them.","aiGenerated":true,"topicCodes":["employment"],"origin":"promoted"},{"id":"lit-aislinn-kelly-lyth-challenging-biased-hiring-algorithm","title":"Challenging Biased Hiring Algorithms","authorsOrOrg":"Aislinn Kelly-Lyth","year":2021,"venue":"Oxford Journal of Legal Studies","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1093/ojls/gqab006","finding":"Evaluates UK equality and data-protection law against algorithmic hiring tools and proposes a 'transparent recruitment scheme' incentivizing publication of equality metrics from data-protection impact assessments.","aiGenerated":true,"topicCodes":["employment"],"origin":"promoted"},{"id":"lit-aislinn-kelly-lyth-algorithmic-discrimination-at-work","title":"Algorithmic discrimination at work","authorsOrOrg":"Aislinn Kelly-Lyth","year":2023,"venue":"European Labour Law Journal","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1177/20319525231167300","finding":"Argues existing European equality law is 'remarkably robust' against algorithmic management discrimination but that opacity and enforcement gaps blunt its effect, mapping where reform is needed.","aiGenerated":true,"topicCodes":["employment"],"origin":"promoted"},{"id":"lit-valerio-de-stefano-and-simon-taes-algorithmic-manageme","title":"Algorithmic management and collective bargaining","authorsOrOrg":"Valerio De Stefano and Simon Taes","year":2023,"venue":"Transfer: European Review of Labour and Research","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1177/10242589221141055","finding":"Argues collective bargaining and worker co-determination, not just individual data rights, are essential governance tools for regulating AI-driven algorithmic management at work.","aiGenerated":true,"topicCodes":["employment"],"origin":"promoted"},{"id":"lit-sandra-fredman-darcy-du-toit-alessio-bertolini-jonas-v","title":"Fair Work for Platform Workers: Lessons from the EU Directive and Beyond","authorsOrOrg":"Sandra Fredman, Darcy Du Toit, Alessio Bertolini, Jonas Valente and Mark Graham","year":2025,"venue":"Industrial Law Journal","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1093/indlaw/dwaf018","finding":"Analyzes the 2024 EU Platform Work Directive through Fairwork evidence, assessing its employment-status and algorithmic-management provisions and charting a path toward a proposed ILO platform-work Convention.","aiGenerated":true,"topicCodes":["employment"],"origin":"promoted"},{"id":"lit-natalie-sheard-algorithm-facilitated-discrimination-a","title":"Algorithm-facilitated discrimination: a socio-legal study of the use by employers of artificial intelligence hiring systems","authorsOrOrg":"Natalie Sheard","year":2025,"venue":"Journal of Law and Society","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1111/jols.12535","finding":"Empirical socio-legal study of employer AI hiring systems showing how design and deployment choices generate discrimination that current anti-discrimination law struggles to reach.","aiGenerated":true,"topicCodes":["employment"],"origin":"promoted"},{"id":"lit-alexander-k-kofinas-crystal-han-huei-tsay-and-david-pi","title":"The impact of generative AI on academic integrity of authentic assessments within a higher education context","authorsOrOrg":"Alexander K. Kofinas, Crystal Han-Huei Tsay and David Pike","year":2025,"venue":"British Journal of Educational Technology","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1111/bjet.13585","finding":"Demonstrates empirically that authentic assessment alone does not safeguard academic integrity against generative AI, implying institutions need policy-level redesign rather than reliance on assessment format.","aiGenerated":true,"topicCodes":["education"],"origin":"promoted"},{"id":"lit-richard-arum-maria-calderon-leon-xunfei-li-and-jomar-l","title":"ChatGPT Early Adoption in Higher Education: Variation in Student Usage, Instructional Support, and Educational Equity","authorsOrOrg":"Richard Arum, Maria Calderon Leon, XunFei Li and Jomar Lopes","year":2025,"venue":"AERA Open","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1177/23328584251331956","finding":"Survey at a diverse U.S. public research university finds ChatGPT adoption and instructor support vary by student demographics and field, raising educational-equity concerns for AI-in-education policy.","aiGenerated":true,"topicCodes":["education"],"origin":"promoted"},{"id":"lit-qi-xia-xiaojing-weng-fan-ouyang-tzung-jin-lin-and-thom","title":"A scoping review on how generative artificial intelligence transforms assessment in higher education","authorsOrOrg":"Qi Xia, Xiaojing Weng, Fan Ouyang, Tzung-Jin Lin and Thomas K.F. Chiu","year":2024,"venue":"International Journal of Educational Technology in Higher Ed","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1186/s41239-024-00468-z","finding":"Reviews 32 empirical studies and concludes assessment should be transformed to cultivate self-regulated, responsible learning and integrity rather than relying on AI-text detection alone.","aiGenerated":true,"topicCodes":["education"],"origin":"promoted"},{"id":"lit-hyunkyung-chee-solmoe-ahn-and-jihyun-lee-a-competency","title":"A Competency Framework for AI Literacy: Variations by Different Learner Groups and an Implied Learning Pathway","authorsOrOrg":"Hyunkyung Chee, Solmoe Ahn and Jihyun Lee","year":2025,"venue":"British Journal of Educational Technology","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1111/bjet.13556","finding":"Systematic review (29 studies) builds an AI-literacy competency framework varying by learner group, offering a reference for designing AI curricula and education-policy learning pathways.","aiGenerated":true,"topicCodes":["education"],"origin":"promoted"},{"id":"lit-tom-folt-nek-sonja-bjelobaba-irene-glendinning-zeenath","title":"ENAI Recommendations on the ethical use of Artificial Intelligence in Education","authorsOrOrg":"Tomáš Foltýnek, Sonja Bjelobaba, Irene Glendinning, Zeenath Reza Khan, Rita Santos, Pegi Pavletic and Július Kravjar","year":2023,"venue":"International Journal for Educational Integrity","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s40979-023-00133-4","finding":"European Network for Academic Integrity policy recommendations: institutions should set transparent rules on permitted AI use, require disclosure, and not penalize tools for tasks they were authorized for.","aiGenerated":true,"topicCodes":["education"],"origin":"promoted"},{"id":"lit-heather-johnston-rebecca-f-wells-elizabeth-m-shanks-ti","title":"Student perspectives on the use of generative artificial intelligence technologies in higher education","authorsOrOrg":"Heather Johnston, Rebecca F. Wells, Elizabeth M. Shanks, Timothy Boey and Bryony N. Parsons","year":2024,"venue":"International Journal for Educational Integrity","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s40979-024-00149-4","finding":"Survey informing the University of Liverpool integrity code finds 54.1% support tools like Grammarly but 70.4% oppose using ChatGPT to write whole essays, guiding nuanced AI-use policy.","aiGenerated":true,"topicCodes":["education"],"origin":"promoted"},{"id":"lit-oscar-freyer-isabella-catharina-wiest-jakob-nikolas-ka","title":"A future role for health applications of large language models depends on regulators enforcing safety standards","authorsOrOrg":"Oscar Freyer, Isabella Catharina Wiest, Jakob Nikolas Kather, Stephen Gilbert","year":2024,"venue":"The Lancet Digital Health","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1016/S2589-7500(24)00124-9","finding":"Argues medical LLMs are likely device-like clinical decision support and that 'the urgent need to enforce existing regulations' is the key safeguard against unsafe deployment.","aiGenerated":true,"topicCodes":["healthcare"],"origin":"promoted"},{"id":"lit-gary-e-weissman-toni-mankowitz-genevieve-p-kanter-unre","title":"Unregulated large language models produce medical device-like output","authorsOrOrg":"Gary E. Weissman, Toni Mankowitz, Genevieve P. Kanter","year":2025,"venue":"npj Digital Medicine","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1038/s41746-025-01544-y","finding":"Finds general-purpose LLMs 'readily produced device-like decision support across a range of scenarios,' implying they should fall under medical-device regulation if clinically deployed.","aiGenerated":true,"topicCodes":["healthcare"],"origin":"promoted"},{"id":"lit-alexey-youssef-michael-pencina-anshul-thakur-tingting","title":"External validation of AI models in health should be replaced with recurring local validation","authorsOrOrg":"Alexey Youssef, Michael Pencina, Anshul Thakur, Tingting Zhu, David Clifton, Nigam H. Shah","year":2023,"venue":"Nature Medicine","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1038/s41591-023-02540-z","finding":"Contends external validation 'does not guarantee generalizability' and proposes recurring local validation as the safer regulatory paradigm for clinical AI.","aiGenerated":true,"topicCodes":["healthcare"],"origin":"promoted"},{"id":"lit-stephen-gilbert-matthew-fenech-martin-hirsch-shubhanan","title":"Algorithm Change Protocols in the Regulation of Adaptive Machine Learning-Based Medical Devices","authorsOrOrg":"Stephen Gilbert, Matthew Fenech, Martin Hirsch, Shubhanan Upadhyay, Andrea Biasiucci, Johannes Starlinger","year":2021,"venue":"Journal of Medical Internet Research","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.2196/30545","finding":"Analyzes the SaMD prespecification and algorithm change protocol mechanism (FDA predetermined change control) for governing continuously-learning medical-device algorithms.","aiGenerated":true,"topicCodes":["healthcare"],"origin":"promoted"},{"id":"lit-boris-babic-i-glenn-cohen-ariel-dora-stern-yiwen-li-me","title":"A general framework for governing marketed AI/ML medical devices","authorsOrOrg":"Boris Babic, I. Glenn Cohen, Ariel Dora Stern, Yiwen Li, Melissa Ouellet","year":2025,"venue":"npj Digital Medicine","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1038/s41746-025-01717-9","finding":"Proposes a post-market governance framework for AI/ML medical devices addressing performance drift and ongoing monitoring beyond initial approval.","aiGenerated":true,"topicCodes":["healthcare"],"origin":"promoted"},{"id":"lit-bertalan-mesk-eric-j-topol-the-imperative-for-regulato","title":"The imperative for regulatory oversight of large language models (or generative AI) in healthcare","authorsOrOrg":"Bertalan Meskó, Eric J. Topol","year":2023,"venue":"npj Digital Medicine","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1038/s41746-023-00873-0","finding":"Calls for a new regulatory category/oversight for medical LLMs, warning existing device frameworks were not designed for general-purpose generative models.","aiGenerated":true,"topicCodes":["healthcare"],"origin":"promoted"},{"id":"lit-vijaytha-muralidharan-madelena-y-ng-shada-alsalamah-sa","title":"Global Initiative on AI for Health (GI-AI4H): strategic priorities advancing governance across the United Nations","authorsOrOrg":"Vijaytha Muralidharan, Madelena Y. Ng, Shada AlSalamah, Sameer Pujari, et al. (WHO/ITU GI-AI4H)","year":2025,"venue":"npj Digital Medicine","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1038/s41746-025-01618-x","finding":"Sets out the WHO/ITU Global Initiative on AI for Health's strategic priorities to harmonize international regulatory and governance standards for health AI.","aiGenerated":true,"topicCodes":["healthcare"],"origin":"promoted"},{"id":"lit-aditya-loganathan-michael-friedman-tayab-waseem-et-al","title":"Current state of Food and Drug Administration-approved artificial intelligence/machine learning medical devices: pathways, transparency, and evidence gaps","authorsOrOrg":"Aditya Loganathan, Michael Friedman, Tayab Waseem, et al. (Andrew C. Meltzer, senior author)","year":2026,"venue":"Journal of Medical Artificial Intelligence","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.21037/jmai-2025-196","finding":"Documents that most FDA AI/ML devices clear via the 510(k) pathway with limited clinical validation and poor transparency, exposing regulatory evidence gaps.","aiGenerated":true,"topicCodes":["healthcare"],"origin":"promoted"},{"id":"lit-doni-bloomfield-jaspreet-pannu-alex-w-zhu-madelena-y-n","title":"AI and biosecurity: The need for governance","authorsOrOrg":"Doni Bloomfield, Jaspreet Pannu, Alex W. Zhu, Madelena Y. Ng, Ashley Lewis, Eran Bendavid, Steven M. Asch, Tina Hernandez-Boussard, Anita Cicero, Tom Inglesby","year":2024,"venue":"Science","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1126/science.adq1977","finding":"Argues 'governments should evaluate advanced [biological] models and if needed impose safety measures' to mitigate AI-enabled biosecurity catastrophic risk.","aiGenerated":true,"topicCodes":["catastrophic_risk"],"origin":"promoted"},{"id":"lit-kirolos-eskandar-artificial-intelligence-and-synthetic","title":"Artificial intelligence and synthetic biology: biosecurity risks, dual-use concerns, and governance pathways","authorsOrOrg":"Kirolos Eskandar","year":2026,"venue":"AI and Ethics (Springer)","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s43681-025-00872-9","finding":"Reviews biosecurity and dual-use risks at the AI-synthetic-biology interface and maps governance pathways for emerging catastrophic threats.","aiGenerated":true,"topicCodes":["catastrophic_risk"],"origin":"promoted"},{"id":"lit-atoosa-kasirzadeh-two-types-of-ai-existential-risk-dec","title":"Two types of AI existential risk: decisive and accumulative","authorsOrOrg":"Atoosa Kasirzadeh","year":2025,"venue":"Philosophical Studies","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s11098-025-02301-3","finding":"Distinguishes 'decisive' (sudden takeover) from 'accumulative' AI existential risk, arguing governance must address gradual societal erosion as well as abrupt scenarios.","aiGenerated":true,"topicCodes":["catastrophic_risk"],"origin":"promoted"},{"id":"lit-bryan-druzin-anatole-boute-michael-ramsden-confronting","title":"Confronting Catastrophic Risk: The International Obligation to Regulate Artificial Intelligence","authorsOrOrg":"Bryan Druzin, Anatole Boute, Michael Ramsden","year":2025,"venue":"Michigan Journal of International Law","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://repository.law.umich.edu/mjil/vol46/iss2/2/","finding":"Argues international law imposes a precautionary-principle obligation on states to regulate AI to mitigate the threat of human extinction.","aiGenerated":true,"topicCodes":["catastrophic_risk"],"origin":"promoted"},{"id":"lit-david-m-allison-stephen-herzog-artificial-intelligence","title":"Artificial Intelligence and Nuclear Weapons Proliferation: The Technological Arms Race for (In)visibility","authorsOrOrg":"David M. Allison, Stephen Herzog","year":2025,"venue":"Risk Analysis","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1111/risa.70105","finding":"Analyzes how AI-driven detection/concealment in nuclear arsenals reshapes strategic stability and proliferation risk, with governance implications.","aiGenerated":true,"topicCodes":["catastrophic_risk"],"origin":"promoted"},{"id":"lit-jonas-schuett-markus-anderljung-alexis-carlier-leonie","title":"From Principles to Rules: A Regulatory Approach for Frontier AI","authorsOrOrg":"Jonas Schuett, Markus Anderljung, Alexis Carlier, Leonie Koessler, Ben Garfinkel (Centre for the Governance of AI)","year":2024,"venue":"arXiv (GovAI working paper)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2407.07300","finding":"Recommends frontier-AI regulation begin with high-level safety principles and migrate to detailed rules (e.g., mandated dangerous-capability evaluations) as regulatory capacity matures.","aiGenerated":true,"topicCodes":["catastrophic_risk"],"origin":"promoted"},{"id":"lit-rebecca-scholefield-samuel-martin-otto-barten-internat","title":"International Agreements on AI Safety: Review and Recommendations for a Conditional AI Safety Treaty","authorsOrOrg":"Rebecca Scholefield, Samuel Martin, Otto Barten","year":2025,"venue":"arXiv (cs.CY)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2503.18956","finding":"Proposes a conditional AI safety treaty with a compute threshold triggering mandatory audits by an international network of AI Safety Institutes empowered to halt development if risks are unacceptable.","aiGenerated":true,"topicCodes":["catastrophic_risk"],"origin":"promoted"},{"id":"lit-alan-chan-noam-kolt-peter-wills-usman-anwar-christian","title":"IDs for AI Systems","authorsOrOrg":"Alan Chan, Noam Kolt, Peter Wills, Usman Anwar, Christian Schroeder de Witt, Nitarshan Rajkumar, Lewis Hammond, David Krueger, Lennart Heim, Markus Anderljung","year":2024,"venue":"arXiv (cs.CY; GovAI/MILA)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2406.12137","finding":"Proposes ascribing IDs to instances of AI systems so users can verify safety certifications, investigate incidents, and enable oversight of agentic deployments.","aiGenerated":true,"topicCodes":["agentic_systems_governance"],"origin":"promoted"},{"id":"lit-tobin-south-samuele-marro-thomas-hardjono-robert-mahar","title":"Authenticated Delegation and Authorized AI Agents","authorsOrOrg":"Tobin South, Samuele Marro, Thomas Hardjono, Robert Mahari, Cedric Deslandes Whitney, Dazza Greenwood, Alan Chan, Alex Pentland","year":2025,"venue":"arXiv (cs.CY; MIT)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2501.09674","finding":"Introduces a framework for authenticated, authorized, and auditable delegation to AI agents by extending OAuth 2.0/OpenID Connect, maintaining accountability chains for agent actions.","aiGenerated":true,"topicCodes":["agentic_systems_governance"],"origin":"promoted"},{"id":"lit-maksym-andriushchenko-alexandra-souly-mateusz-dziemian","title":"AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents","authorsOrOrg":"Maksym Andriushchenko, Alexandra Souly, Mateusz Dziemian, Derek Duenas, Maxwell Lin, Justin Wang, Dan Hendrycks, Andy Zou, Zico Kolter, Matt Fredrikson, Eric Winsor, Jerome Wynne, Yarin Gal, Xander Davies (UK AISI / Gray Swan)","year":2025,"venue":"ICLR 2025","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://arxiv.org/abs/2410.09024","finding":"Provides a 440-task benchmark across 11 harm categories measuring whether LLM agents resist or comply with harmful multi-step tool-use tasks, grounding safety-evaluation regimes for agents.","aiGenerated":true,"topicCodes":["agentic_systems_governance"],"origin":"promoted"},{"id":"lit-sumeet-ramesh-motwani-mikhail-baranchuk-martin-strohme","title":"Secret Collusion among AI Agents: Multi-Agent Deception via Steganography","authorsOrOrg":"Sumeet Ramesh Motwani, Mikhail Baranchuk, Martin Strohmeier, Vijay Bolina, Philip H.S. Torr, Lewis Hammond, Christian Schroeder de Witt","year":2024,"venue":"arXiv (NeurIPS 2024)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2402.07510","finding":"Shows LLM agents can use steganography to communicate covertly, exposing a monitoring/oversight gap for governing multi-agent systems and motivating ongoing mitigation.","aiGenerated":true,"topicCodes":["agentic_systems_governance"],"origin":"promoted"},{"id":"lit-ana-maria-corr-a-sara-garsia-abdullah-elbi-better-toge","title":"Better together? Human oversight as means to achieve fairness in the European AI Act governance","authorsOrOrg":"Ana Maria Corrêa, Sara Garsia, Abdullah Elbi","year":2025,"venue":"Cambridge Forum on AI: Law and Governance","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1017/cfl.2025.10010","finding":"Examines whether Article-14 human oversight of high-risk/autonomous AI can actually deliver fairness, probing the limits of human-in-the-loop as a governance mechanism.","aiGenerated":true,"topicCodes":["agentic_systems_governance"],"origin":"promoted"},{"id":"lit-shayne-longpre-sayash-kapoor-kevin-klyman-rishi-bommas","title":"A Safe Harbor for AI Evaluation and Red Teaming","authorsOrOrg":"Shayne Longpre, Sayash Kapoor, Kevin Klyman, Rishi Bommasani, Arvind Narayanan, Percy Liang, Peter Henderson, et al.","year":2024,"venue":"arXiv (ICML 2024)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2403.04893","finding":"Proposes legal and technical safe-harbor protections so independent researchers can conduct good-faith safety evaluation and red-teaming of AI agents/systems without ToS reprisal.","aiGenerated":true,"topicCodes":["agentic_systems_governance"],"origin":"promoted"},{"id":"lit-taner-kuru-lawfulness-of-the-mass-processing-of-public","title":"Lawfulness of the mass processing of publicly accessible online data to train large language models","authorsOrOrg":"Taner Kuru","year":2024,"venue":"International Data Privacy Law","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1093/idpl/ipae013","finding":"Argues LLM training on scraped web data should be assessed under Art. 9 GDPR (sensitive data), and that consent and the 'manifestly made public' route leave only a 'limited amount of personal data' lawfully usable.","aiGenerated":true,"topicCodes":["training_data"],"origin":"promoted"},{"id":"lit-martin-kretschmer-bartolomeo-meletti-lionel-bently-gab","title":"Copyright and AI in the UK: Opting-In or Opting-Out?","authorsOrOrg":"Martin Kretschmer, Bartolomeo Meletti, Lionel Bently, Gabriele Cifrodelli, Magali Eben, Kristofer Erickson, Aline Iramina, Zihao Li, Luke McDonagh, Emma Perot, Luis Porangaba, Amy Thomas","year":2025,"venue":"GRUR International","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1093/grurint/ikaf093","finding":"Contends the UK opt-in/opt-out framing is a 'missed opportunity'; a broadened research exception plus market-entry transparency and creator remuneration would better serve both innovation and rightsholders.","aiGenerated":true,"topicCodes":["training_data"],"origin":"promoted"},{"id":"lit-arne-radeisen-open-foundation-models-and-tdm-exception","title":"Open Foundation Models and TDM Exceptions to Copyright – Building Blocks for an AI Ecosystem","authorsOrOrg":"Arne Radeisen","year":2026,"venue":"GRUR International","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1093/grurint/ikag002","finding":"Argues Art. 3 CDSM Directive's scientific-research TDM exception 'does not grant rightsholders any control' and can be a 'safe harbor' for training openly released foundation models without licensing data.","aiGenerated":true,"topicCodes":["training_data"],"origin":"promoted"},{"id":"lit-kaigeng-li-hong-wu-yupeng-dong-copyright-protection-du","title":"Copyright protection during the training stage of generative AI: Industry-oriented U.S. law, rights-oriented EU law, and fair remuneration rights for generative AI training under the UN's international governance regime for AI","authorsOrOrg":"Kaigeng Li, Hong Wu, Yupeng Dong","year":2024,"venue":"Computer Law & Security Review, 55","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1016/j.clsr.2024.106056","finding":"Comparatively maps US (industry-oriented fair use), EU (rights-oriented TDM opt-out) and a proposed UN fair-remuneration approach to copyright at the generative-AI training stage.","aiGenerated":true,"topicCodes":["training_data"],"origin":"promoted"},{"id":"lit-matthew-sag-fairness-and-fair-use-in-generative-ai","title":"Fairness and Fair Use in Generative AI","authorsOrOrg":"Matthew Sag","year":2024,"venue":"Fordham Law Review","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://ir.lawnet.fordham.edu/flr/vol92/iss5/7/","finding":"Rejects blanket lawful/unlawful verdicts on AI training, proposing 'an analytical framework for making that assessment in particular cases' for where owners' rights end and use freedoms begin.","aiGenerated":true,"topicCodes":["training_data"],"origin":"promoted"},{"id":"lit-stepanka-havlikova-technical-challenges-of-rightsholde","title":"Technical Challenges of Rightsholders' Opt-out From Gen AI Training after Robert Kneschke v. LAION","authorsOrOrg":"Stepanka Havlikova","year":2025,"venue":"JIPITEC – Journal of Intellectual Property, Information Tech","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://www.jipitec.eu/jipitec/article/view/422","finding":"Examines post-LAION practical obstacles to the EU TDM opt-out (robots.txt, machine-readability, memorisation): 'While the TDM exceptions may seem workable in theory, implementing them in practice presents a variety of practical…","aiGenerated":true,"topicCodes":["training_data"],"origin":"promoted"},{"id":"lit-shayne-longpre-robert-mahari-ariel-lee-et-al-consent-i","title":"Consent in Crisis: The Rapid Decline of the AI Data Commons","authorsOrOrg":"Shayne Longpre, Robert Mahari, Ariel Lee, et al.","year":2024,"venue":"arXiv (Data Provenance Initiative; presented NeurIPS Dataset","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2407.14933","finding":"Longitudinal audit of 14,000 web domains finds a 2023-24 surge in AI training restrictions, with '~5%+ of all tokens in C4...fully restricted from use' within a single year.","aiGenerated":true,"topicCodes":["training_data"],"origin":"promoted"},{"id":"lit-national-telecommunications-and-information-administra","title":"Dual-Use Foundation Models with Widely Available Model Weights (NTIA Report)","authorsOrOrg":"National Telecommunications and Information Administration (NTIA), U.S. Department of Commerce","year":2024,"venue":"NTIA / U.S. Department of Commerce","evidenceType":"research_institute","evidenceTypeLabel":"Research institute","url":"https://www.ntia.gov/sites/default/files/publications/ntia-ai-open-model-report.pdf","finding":"Recommends the US government monitor but not currently restrict open-weight models, assessing case-by-case whether 'marginal risks' over closed models or pre-existing technology warrant action.","aiGenerated":true,"topicCodes":["open_weight_release"],"origin":"promoted"},{"id":"lit-toby-shevlane-structured-access-an-emerging-paradigm-f-2","title":"Structured Access: An Emerging Paradigm for Safe AI Deployment","authorsOrOrg":"Toby Shevlane","year":2022,"venue":"The Oxford Handbook of AI Governance (OUP)","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1093/oxfordhb/9780197579329.013.39","finding":"Proposes 'structured access' (controlled, arm's-length cloud interactions) as a middle path between open release and full closure, restricting dangerous capabilities while preserving beneficial use and scrutiny.","aiGenerated":true,"topicCodes":["open_weight_release"],"origin":"promoted"},{"id":"lit-irene-solaiman-miles-brundage-jack-clark-amanda-askell","title":"Release Strategies and the Social Impacts of Language Models","authorsOrOrg":"Irene Solaiman, Miles Brundage, Jack Clark, Amanda Askell, et al.","year":2019,"venue":"arXiv (OpenAI)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/1908.09203","finding":"Documents OpenAI's GPT-2 staged-release experiment, arguing 'staged release allows time between model releases to conduct risk and benefit analyses' and proposing publication norms for powerful models.","aiGenerated":true,"topicCodes":["open_weight_release"],"origin":"promoted"},{"id":"lit-david-gray-widder-sarah-west-meredith-whittaker-open-f","title":"Open (For Business): Big Tech, Concentrated Power, and the Political Economy of Open AI","authorsOrOrg":"David Gray Widder, Sarah West, Meredith Whittaker","year":2023,"venue":"SSRN Electronic Journal","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://doi.org/10.2139/ssrn.4543807","finding":"Argues 'even the most open of open AI systems do not, on their own, ensure democratic access...nor does openness alone solve the problem of oversight,' and that openness rhetoric can entrench Big Tech power.","aiGenerated":true,"topicCodes":["open_weight_release"],"origin":"promoted"},{"id":"lit-andreas-liesenfeld-mark-dingemanse-rethinking-open-sou","title":"Rethinking open source generative AI: open-washing and the EU AI Act","authorsOrOrg":"Andreas Liesenfeld, Mark Dingemanse","year":2024,"venue":"Proceedings of the 2024 ACM Conference on Fairness, Accounta","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3630106.3659005","finding":"A 14-dimension survey of 45+ systems finds many self-described 'open source' models are 'open weight at best' and providers seek to 'evade scientific, legal and regulatory scrutiny' under the EU AI Act's open-source exemption.","aiGenerated":true,"topicCodes":["open_weight_release"],"origin":"promoted"},{"id":"lit-alan-chan-ben-bucknall-herbie-bradley-et-al-hazards-fr","title":"Hazards from Increasingly Accessible Fine-Tuning of Downloadable Foundation Models","authorsOrOrg":"Alan Chan, Ben Bucknall, Herbie Bradley, et al.","year":2023,"venue":"arXiv","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2312.14751","finding":"Grounds the open-weight marginal-risk debate technically: 'increasingly accessible fine-tuning methods may increase hazard through facilitating malicious use and making oversight...more difficult.'","aiGenerated":true,"topicCodes":["open_weight_release"],"origin":"promoted"},{"id":"lit-xiangyu-qi-boyi-wei-nicholas-carlini-et-al-on-evaluati","title":"On Evaluating the Durability of Safeguards for Open-Weight LLMs","authorsOrOrg":"Xiangyu Qi, Boyi Wei, Nicholas Carlini, et al.","year":2024,"venue":"arXiv","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2412.07097","finding":"Shows tamper-resistance safeguards for open weights are fragile and hard to assess, cautioning that 'even evaluating these defenses is exceedingly difficult and can easily mislead audiences' — undercutting safeguard-conditioned…","aiGenerated":true,"topicCodes":["open_weight_release"],"origin":"promoted"},{"id":"lit-mark-robinson-the-establishment-of-an-international-ai","title":"The establishment of an international AI agency: an applied solution to global AI governance","authorsOrOrg":"Mark Robinson","year":2025,"venue":"International Affairs","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1093/ia/iiaf105","finding":"Proposes a UN-backed International Artificial Intelligence Agency modelled on the IAEA, arguing 'only an IAIA can legitimately oversee a global AI governance framework involving all major powers.'","aiGenerated":true,"topicCodes":["international_coordination"],"origin":"promoted"},{"id":"lit-council-of-europe-introductory-note-by-marc-rotenberg","title":"Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law (Council Eur.) — with Introductory Note","authorsOrOrg":"Council of Europe; Introductory Note by Marc Rotenberg","year":2025,"venue":"International Legal Materials","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1017/ilm.2025.1","finding":"Reproduces and annotates the first legally binding international AI treaty, grounding cross-border AI governance in legality, proportionality, transparency, accountability and non-discrimination across the AI lifecycle.","aiGenerated":true,"topicCodes":["international_coordination"],"origin":"promoted"},{"id":"lit-akash-r-wasil-peter-barnett-michael-gerovitch-roman-ha","title":"Governing dual-use technologies: Case studies of international security agreements and lessons for AI governance","authorsOrOrg":"Akash R. Wasil, Peter Barnett, Michael Gerovitch, Roman Hauksson, Tom Reed, Jack William Miller","year":2024,"venue":"arXiv (also SSRN)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2409.02779","finding":"Mines nuclear, chemical, biosecurity and export-control regimes for institutional-design lessons for AI agreements, emphasising 'robust verification methods, strategies for balancing power between nations' and enforcement.","aiGenerated":true,"topicCodes":["international_coordination"],"origin":"promoted"},{"id":"lit-emma-klein-stewart-patrick-carnegie-endowment-for-inte","title":"Envisioning a Global Regime Complex to Govern Artificial Intelligence","authorsOrOrg":"Emma Klein, Stewart Patrick (Carnegie Endowment for International Peace)","year":2024,"venue":"Carnegie Endowment for International Peace","evidenceType":"think_tank","evidenceTypeLabel":"Think tank","url":"https://carnegieendowment.org/research/2024/03/envisioning-a-global-regime-complex-to-govern-artificial-intelligence","finding":"Argues AI governance will not be a single institution but 'something less elegant: a regime complex' of overlapping arrangements for science, standards, benefit-sharing and collective security.","aiGenerated":true,"topicCodes":["international_coordination"],"origin":"promoted"},{"id":"lit-stephen-weymouth-digital-disintegration-techno-blocs-a","title":"Digital Disintegration: Techno-Blocs and Strategic Sovereignty in the AI Era","authorsOrOrg":"Stephen Weymouth","year":2025,"venue":"International Organization","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1017/S0020818325101070","finding":"Argues states increasingly assert 'strategic digital sovereignty...through selective alliances with firms and other governments,' fragmenting global AI infrastructure into techno-blocs rather than multilateral order.","aiGenerated":true,"topicCodes":["international_coordination","sovereign_ai"],"origin":"promoted"},{"id":"lit-roxana-radu-steering-the-governance-of-artificial-inte","title":"Steering the governance of artificial intelligence: national strategies in perspective","authorsOrOrg":"Roxana Radu","year":2021,"venue":"Policy and Society","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1080/14494035.2021.1929728","finding":"Qualitative content analysis of ~12 national AI strategies (2017-2019) shows governments deploy 'sovereigntist AI projects' that reconfigure public-private ordering via hybrid governance and marketization.","aiGenerated":true,"topicCodes":["sovereign_ai"],"origin":"promoted"},{"id":"lit-jascha-bareis-christian-katzenbach-talking-ai-into-bei","title":"Talking AI into Being: The Narratives and Imaginaries of National AI Strategies and Their Performative Politics","authorsOrOrg":"Jascha Bareis, Christian Katzenbach","year":2021,"venue":"Science, Technology, & Human Values","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1177/01622439211030007","finding":"Comparing China, US, France and Germany strategies, the authors show national AI policy documents 'talk AI into being' through competing sovereignty/leadership imaginaries that perform political reality.","aiGenerated":true,"topicCodes":["sovereign_ai"],"origin":"promoted"},{"id":"lit-guy-paltieli-the-political-imaginary-of-national-ai-st","title":"The political imaginary of National AI Strategies","authorsOrOrg":"Guy Paltieli","year":2022,"venue":"AI & Society","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s00146-021-01258-1","finding":"National AI strategies mobilize democratic, sociotechnical and data imaginaries that frame sovereign AI capacity as a means for democracies to overcome governance challenges.","aiGenerated":true,"topicCodes":["sovereign_ai"],"origin":"promoted"},{"id":"lit-justin-kollar-andrew-stokols-geopolitical-ecologies-of","title":"Geopolitical ecologies of cloud capitalism: Territorial restructuring and the making of national computing power in the U.S. and China","authorsOrOrg":"Justin Kollar, Andrew Stokols","year":2026,"venue":"Environment and Planning A: Economy and Space","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1177/0308518X251369704","finding":"US and Chinese drives for sovereign AI/cloud dominance depend on reorganizing land, energy and regulatory systems to sustain large-scale national computing power.","aiGenerated":true,"topicCodes":["sovereign_ai"],"origin":"promoted"},{"id":"lit-nur-ahmed-muntasir-wahed-the-de-democratization-of-ai","title":"The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research","authorsOrOrg":"Nur Ahmed, Muntasir Wahed","year":2020,"venue":"arXiv preprint arXiv:2010.15581","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2010.15581","finding":"Analysis of 171,394 papers shows access to compute drives a 'compute divide' concentrating AI capacity in large firms and elite universities, de-democratizing knowledge production.","aiGenerated":true,"topicCodes":["sovereign_ai"],"origin":"promoted"},{"id":"lit-daniel-m-m-gge-eu-ai-sovereignty-for-whom-to-what-end","title":"EU AI sovereignty: for whom, to what end, and to whose benefit?","authorsOrOrg":"Daniel M. Mügge","year":2024,"venue":"Journal of European Public Policy","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1080/13501763.2024.2318475","finding":"Interrogates the EU 'AI sovereignty' agenda, showing the goal is under-specified and risks serving incumbent industrial interests rather than European publics.","aiGenerated":true,"topicCodes":["tech_sovereignty"],"origin":"promoted"},{"id":"lit-andrea-calderaro-stella-blumfelde-artificial-intellige","title":"Artificial intelligence and EU security: the false promise of digital sovereignty","authorsOrOrg":"Andrea Calderaro, Stella Blumfelde","year":2022,"venue":"European Security","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1080/09662839.2022.2101885","finding":"Argues the EU's pursuit of AI-based digital sovereignty in security is a 'false promise' given dependence on non-EU compute, data and chip supply chains.","aiGenerated":true,"topicCodes":["tech_sovereignty"],"origin":"promoted"},{"id":"lit-rebecca-adler-nissen-kristin-anabel-eggeling-the-discu","title":"The Discursive Struggle for Digital Sovereignty: Security, Economy, Rights and the Cloud Project Gaia-X","authorsOrOrg":"Rebecca Adler-Nissen, Kristin Anabel Eggeling","year":2024,"venue":"JCMS: Journal of Common Market Studies","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1111/jcms.13594","finding":"Case study of Gaia-X finds no singular EU meaning of digital sovereignty but six competing conceptions across security, economy and rights domains.","aiGenerated":true,"topicCodes":["tech_sovereignty"],"origin":"promoted"},{"id":"lit-andreas-baur-european-ambitions-captured-by-american-c","title":"European ambitions captured by American clouds: digital sovereignty through Gaia-X?","authorsOrOrg":"Andreas Baur","year":2026,"venue":"Information, Communication & Society","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1080/1369118X.2025.2516545","finding":"Shows Gaia-X paradoxically incorporates dominant US cloud providers, undermining the very European digital sovereignty it was meant to advance.","aiGenerated":true,"topicCodes":["tech_sovereignty"],"origin":"promoted"},{"id":"lit-patrik-hummel-matthias-braun-max-tretter-peter-dabrock","title":"Data sovereignty: A review","authorsOrOrg":"Patrik Hummel, Matthias Braun, Max Tretter, Peter Dabrock","year":2021,"venue":"Big Data & Society","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1177/2053951720982012","finding":"Systematic review of 341 publications maps how data, digital and cyber sovereignty are conceptualized and the control challenges they pose across stakeholders.","aiGenerated":true,"topicCodes":["tech_sovereignty"],"origin":"promoted"},{"id":"lit-julia-pohle-riccardo-nanni-mauro-santaniello-unthinkin","title":"Unthinking Digital Sovereignty: A Critical Reflection on Origins, Objectives, and Practices","authorsOrOrg":"Julia Pohle, Riccardo Nanni, Mauro Santaniello","year":2024,"venue":"Policy & Internet","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1002/poi3.437","finding":"Critically traces digital sovereignty's origins and uses, arguing the frame masks contested objectives and should be 'unthought' to clarify governance practice.","aiGenerated":true,"topicCodes":["tech_sovereignty"],"origin":"promoted"},{"id":"lit-timo-seidl-luuk-schmitz-moving-on-to-not-fall-behind-t","title":"Moving on to not fall behind? Technological sovereignty and the 'geo-dirigiste' turn in EU industrial policy","authorsOrOrg":"Timo Seidl, Luuk Schmitz","year":2024,"venue":"Journal of European Public Policy","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1080/13501763.2023.2248204","finding":"Argues technological sovereignty rhetoric drives a 'geo-dirigiste' turn in EU industrial policy (e.g. semiconductors) blending security and competitiveness logics.","aiGenerated":true,"topicCodes":["tech_sovereignty"],"origin":"promoted"},{"id":"lit-james-muldoon-boxi-a-wu-artificial-intelligence-in-the","title":"Artificial Intelligence in the Colonial Matrix of Power","authorsOrOrg":"James Muldoon, Boxi A. Wu","year":2023,"venue":"Philosophy & Technology","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1007/s13347-023-00687-8","finding":"Theorizes AI through Quijano's 'colonial matrix of power', showing global production imbalances extract value from majority-world labor for Northern firms.","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"},{"id":"lit-min-jiang-models-of-state-digital-sovereignty-from-the","title":"Models of State Digital Sovereignty From the Global South: Diverging Experiences From China, India and South Africa","authorsOrOrg":"Min Jiang","year":2024,"venue":"Policy & Internet","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1002/poi3.427","finding":"Comparative analysis finds China, India and South Africa pursue divergent state digital-sovereignty models shaped by distinct development trajectories and rights regimes.","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"},{"id":"lit-jake-okechukwu-effoduh-ugochukwu-ejike-akpudo-jude-dze","title":"Toward a trustworthy and inclusive data governance policy for the use of artificial intelligence in Africa","authorsOrOrg":"Jake Okechukwu Effoduh, Ugochukwu Ejike Akpudo, Jude Dzevela Kong","year":2024,"venue":"Data & Policy","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1017/dap.2024.26","finding":"Proposes five design principles for African-centred AI data governance, warning that reliance on non-African frameworks undermines local and regional inclusivity.","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"},{"id":"lit-thompson-gyedu-kwarkye-we-know-what-we-are-doing-the-p","title":"\"We know what we are doing\": the politics and trends in artificial intelligence policies in Africa","authorsOrOrg":"Thompson Gyedu Kwarkye","year":2025,"venue":"Canadian Journal of African Studies / Revue canadienne des é","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1080/00083968.2025.2456619","finding":"Maps the political drivers and trends of emerging African national AI policies, situating sovereignty and development framings against external dependency.","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"},{"id":"lit-huw-roberts-mariarosaria-taddeo-luciano-floridi-a-fram","title":"A Framework for Evaluating Global AI Governance Initiatives","authorsOrOrg":"Huw Roberts, Mariarosaria Taddeo, Luciano Floridi","year":2026,"venue":"Global Policy","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1111/1758-5899.70164","finding":"Offers a framework to evaluate global AI governance initiatives, recommending capacity-building so Global South states can meaningfully participate in standard-setting.","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"},{"id":"lit-rafael-grohmann-latin-american-critical-data-studies","title":"Latin American critical data studies","authorsOrOrg":"Rafael Grohmann","year":2025,"venue":"Big Data & Society","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1177/20539517251330160","finding":"Surveys Latin American critical data studies, advancing concepts of statistical, epistemic and national sovereignty as decolonial framings for AI/data governance.","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"},{"id":"lit-fernando-filgueiras-designing-artificial-intelligence","title":"Designing artificial intelligence policy: Comparing design spaces in Latin America","authorsOrOrg":"Fernando Filgueiras","year":2023,"venue":"Latin American Policy","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1111/lamp.12282","finding":"Compares AI policy 'design spaces' across Latin American states, showing how development and capacity constraints shape divergent governance choices.","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"},{"id":"lit-abeba-birhane-algorithmic-colonization-of-africa","title":"Algorithmic Colonization of Africa","authorsOrOrg":"Abeba Birhane","year":2020,"venue":"SCRIPTed: A Journal of Law, Technology & Society","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.2966/scrip.170220.389","finding":"Argues Western tech monopolies practice 'algorithmic colonialism' in Africa, with profit-driven AI solutions reproducing colonial power asymmetries.","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"},{"id":"lit-maarten-buyl-alexander-rogiers-sander-noels-et-al-larg","title":"Large language models reflect the ideology of their creators","authorsOrOrg":"Maarten Buyl, Alexander Rogiers, Sander Noels, et al.","year":2026,"venue":"npj Artificial Intelligence","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1038/s44387-025-00048-0","finding":"Empirically shows LLMs encode their creators' ideologies, supporting policy incentives for home-grown models reflecting local cultural views, especially in low-resource-language regions.","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"},{"id":"lit-yoko-mochizuki-eric-bruillard-audrey-bryan-the-ethics","title":"The ethics of AI or techno-solutionism? UNESCO's policy guidance on AI in education","authorsOrOrg":"Yoko Mochizuki, Eric Bruillard, Audrey Bryan","year":2025,"venue":"British Journal of Sociology of Education","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1080/01425692.2025.2502808","finding":"Critiques UNESCO's AI-in-education guidance as techno-solutionism that can facilitate Big Tech access to Global South education under a 'capacity development' framing.","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"},{"id":"lit-monika-zalnieriute-a-struggle-for-competence-national","title":"A Struggle for Competence: National Security, Surveillance and the Scope of EU Law at the Court of Justice of European Union","authorsOrOrg":"Monika Zalnieriute","year":2022,"venue":"The Modern Law Review","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1111/1468-2230.12652","finding":"Analyses how the CJEU in Privacy International and La Quadrature du Net subjected member-state national-security surveillance to EU law, turning the national-security boundary into a contested struggle over competence.","aiGenerated":true,"topicCodes":["national_security_carveouts"],"origin":"promoted"},{"id":"lit-monika-zalnieriute-big-brother-watch-and-others-v-the","title":"Big Brother Watch and Others v. the United Kingdom","authorsOrOrg":"Monika Zalnieriute","year":2022,"venue":"American Journal of International Law","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1017/ajil.2022.35","finding":"Case note on the ECtHR Grand Chamber's first post-Snowden bulk-interception ruling, holding bulk surveillance not per se disproportionate but requiring end-to-end independent oversight safeguards.","aiGenerated":true,"topicCodes":["national_security_carveouts"],"origin":"promoted"},{"id":"lit-roger-clarke-data-retention-as-mass-surveillance-the-n","title":"Data retention as mass surveillance: the need for an evaluative framework","authorsOrOrg":"Roger Clarke","year":2015,"venue":"International Data Privacy Law","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1093/idpl/ipu036","finding":"Argues data-retention mandates justified by national security amount to mass surveillance and proposes an evaluative framework because such 'highly intrusive proposals' lack an agreed basis for assessment.","aiGenerated":true,"topicCodes":["national_security_carveouts"],"origin":"promoted"},{"id":"lit-francesca-palmiotto-the-ai-act-roller-coaster-the-evol","title":"The AI Act Roller Coaster: The Evolution of Fundamental Rights Protection in the Legislative Process and the Future of the Regulation","authorsOrOrg":"Francesca Palmiotto","year":2025,"venue":"European Journal of Risk Regulation","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1017/err.2024.97","finding":"Traces how the AI Act's law-enforcement and national-security exceptions widened during negotiations, producing 'double standards for fundamental rights protection' and gaps in the regulatory framework.","aiGenerated":true,"topicCodes":["national_security_carveouts"],"origin":"promoted"},{"id":"lit-ezgi-yazici-toward-a-global-standard-for-ethical-ai-re","title":"Toward a global standard for ethical AI regulation: addressing gaps in AI-driven biometric and high-resolution satellite imaging in the EU AI Act","authorsOrOrg":"Ezgi Yazici","year":2025,"venue":"Law, Innovation and Technology","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1080/17579961.2025.2470589","finding":"Identifies how the AI Act's military, defence and national-security exclusions leave biometric and satellite-imaging surveillance under-regulated, arguing for a global standard to close these gaps.","aiGenerated":true,"topicCodes":["national_security_carveouts"],"origin":"promoted"},{"id":"lit-chiara-gallese-predictive-policing-and-predictive-just","title":"Predictive policing and predictive justice: Ethics, data protection, and the AI act","authorsOrOrg":"Chiara Gallese","year":2026,"venue":"Computer Law & Security Review","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1016/j.clsr.2026.106282","finding":"Examines how predictive-policing and predictive-justice systems interact with data-protection law and the AI Act's law-enforcement provisions, exposing accountability and oversight shortfalls.","aiGenerated":true,"topicCodes":["national_security_carveouts"],"origin":"promoted"},{"id":"lit-irena-barkane-lolita-buka-prohibited-ai-surveillance-p","title":"Prohibited AI surveillance practices in the Artificial Intelligence Act: promises and pitfalls in protecting fundamental rights","authorsOrOrg":"Irena Barkane & Lolita Buka","year":2025,"venue":"Critical Perspectives on Predictive Policing (Edward Elgar)","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.4337/9781035323036.00011","finding":"Argues the AI Act's Article 5 surveillance prohibitions are undercut by broad law-enforcement and security exceptions, so 'enforcement of fundamental rights and data protection law' must do the heavy lifting against mass survei…","aiGenerated":true,"topicCodes":["national_security_carveouts"],"origin":"promoted"},{"id":"lit-plixavra-vogiatzoglou-the-ai-act-national-security-exc","title":"The AI Act National Security Exception: room for manoeuvres?","authorsOrOrg":"Plixavra Vogiatzoglou","year":2024,"venue":"Verfassungsblog (EU AI Act's Impact on Security Law debate s","evidenceType":"think_tank","evidenceTypeLabel":"Think tank","url":"https://doi.org/10.59704/292082becc7cc8e6","finding":"Argues the AI Act's exclusion of systems used 'exclusively for military, defence or national security purposes' will be destabilised by the unresolved CJEU/member-state contest over what national security means.","aiGenerated":true,"topicCodes":["national_security_carveouts"],"origin":"promoted"},{"id":"lit-alex-de-vries-the-growing-energy-footprint-of-artifici","title":"The growing energy footprint of artificial intelligence","authorsOrOrg":"Alex de Vries","year":2023,"venue":"Joule","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1016/j.joule.2023.09.004","finding":"Canonical estimate projecting AI servers could consume 85-134 TWh/year by 2027 (comparable to a small country), framing disclosure of AI electricity use as a policy problem.","aiGenerated":true,"topicCodes":["environmental_impact_of_training"],"origin":"promoted"},{"id":"lit-pengfei-li-jianyi-yang-mohammad-a-islam-shaolei-ren-ma","title":"Making AI Less 'Thirsty': Uncovering and Addressing the Secret Water Footprint of AI Models","authorsOrOrg":"Pengfei Li, Jianyi Yang, Mohammad A. Islam, Shaolei Ren","year":2025,"venue":"Communications of the ACM","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3724499","finding":"Estimates training GPT-3 in US data centres can evaporate ~5.4 million litres of water and projects 4.2-6.6 billion m3 of AI water withdrawal by 2027, arguing water use needs reporting and scheduling.","aiGenerated":true,"topicCodes":["environmental_impact_of_training"],"origin":"promoted"},{"id":"lit-lo-c-lannelongue-jason-grealey-michael-inouye-green-al","title":"Green Algorithms: Quantifying the Carbon Footprint of Computation","authorsOrOrg":"Loïc Lannelongue, Jason Grealey, Michael Inouye","year":2021,"venue":"Advanced Science","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1002/advs.202100707","finding":"Provides a standardized, reproducible methodological framework (and calculator) to estimate the carbon footprint of any computational task from runtime, hardware and grid location.","aiGenerated":true,"topicCodes":["environmental_impact_of_training"],"origin":"promoted"},{"id":"lit-alexandra-sasha-luccioni-sylvain-viguier-anne-laure-li","title":"Estimating the Carbon Footprint of BLOOM, a 176B Parameter Language Model","authorsOrOrg":"Alexandra Sasha Luccioni, Sylvain Viguier, Anne-Laure Ligozat","year":2023,"venue":"Journal of Machine Learning Research","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://www.jmlr.org/papers/volume24/23-0069/23-0069.pdf","finding":"Life-cycle estimate finding BLOOM's training emitted ~24.7 tCO2e from dynamic power but ~50.5 tCO2e once manufacturing and idle/operational consumption are counted, motivating full-lifecycle reporting.","aiGenerated":true,"topicCodes":["environmental_impact_of_training"],"origin":"promoted"},{"id":"lit-david-patterson-joseph-gonzalez-quoc-le-chen-liang-llu","title":"Carbon Emissions and Large Neural Network Training","authorsOrOrg":"David Patterson, Joseph Gonzalez, Quoc Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David So, Maud Texier, Jeff Dean","year":2021,"venue":"arXiv (preprint)","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2104.10350","finding":"Computes energy and carbon for T5, Meena, GShard, Switch Transformer and GPT-3, showing operational choices (model, datacentre, hardware, region) can shift training emissions by orders of magnitude.","aiGenerated":true,"topicCodes":["environmental_impact_of_training"],"origin":"promoted"},{"id":"lit-roy-schwartz-jesse-dodge-noah-a-smith-oren-etzioni-gre","title":"Green AI","authorsOrOrg":"Roy Schwartz, Jesse Dodge, Noah A. Smith, Oren Etzioni","year":2020,"venue":"Communications of the ACM","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1145/3381831","finding":"Coins 'Green AI', arguing compute/energy efficiency should be reported as a first-class evaluation metric alongside accuracy to curb the rising environmental cost of deep learning.","aiGenerated":true,"topicCodes":["environmental_impact_of_training"],"origin":"promoted"},{"id":"lit-payal-dhar-the-carbon-impact-of-artificial-intelligenc","title":"The carbon impact of artificial intelligence","authorsOrOrg":"Payal Dhar","year":2020,"venue":"Nature Machine Intelligence","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1038/s42256-020-0219-9","finding":"Surveys evidence that ML's carbon cost is under-measured and calls for tools to quantify training footprints and a shift to sustainable AI infrastructure as a governance priority.","aiGenerated":true,"topicCodes":["environmental_impact_of_training"],"origin":"promoted"},{"id":"lit-andr-ebert-joseph-alder-ralf-herbrich-philipp-hacker-a","title":"AI, Climate, and Regulation: From Data Centers to the AI Act","authorsOrOrg":"André Ebert, Joseph Alder, Ralf Herbrich, Philipp Hacker","year":2026,"venue":"Computer Law & Security Review","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1016/j.clsr.2026.106326","finding":"Analyses the legal levers (AI Act energy-reporting duties, Energy Efficiency Directive data-centre KPIs, sustainability reporting) for governing AI's climate footprint and their disclosure gaps.","aiGenerated":true,"topicCodes":["environmental_impact_of_training"],"origin":"promoted"},{"id":"lit-udit-gupta-young-geun-kim-sylvia-lee-jordan-tse-hsien","title":"Chasing Carbon: The Elusive Environmental Footprint of Computing","authorsOrOrg":"Udit Gupta, Young Geun Kim, Sylvia Lee, Jordan Tse, Hsien-Hsin S. Lee, Gu-Yeon Wei, David Brooks, Carole-Jean Wu","year":2022,"venue":"IEEE Micro","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1109/mm.2022.3163226","finding":"Shows embodied (manufacturing) carbon can rival operational emissions for computing systems, grounding the case that AI footprint accounting and rules must include hardware lifecycle, not just training energy.","aiGenerated":true,"topicCodes":["environmental_impact_of_training"],"origin":"promoted"},{"id":"lit-chan-papyshev-yarime-regulation-innovation-tradeoff","title":"Balancing the tradeoff between regulation and innovation for artificial intelligence: command-and-control vs self-regulatory approaches","authorsOrOrg":"Keith Jin Deng Chan, Gleb Papyshev, Masaru Yarime","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1016/j.techsoc.2024.102747","finding":"Compares top-down command-and-control vs bottom-up self-regulatory AI governance, analysing the regulation-vs-innovation tradeoff a deregulatory order resolves toward removing barriers.","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"},{"id":"lit-cajueiro-celestino-ai-regulation-ethics-innovation-review","title":"A comprehensive review of Artificial Intelligence regulation: Weighing ethical principles and innovation","authorsOrOrg":"Daniel Oliveira Cajueiro, Victor Rafael Rezende Celestino","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1016/j.ject.2025.07.001","finding":"A 60-reference review weighing AI innovation and economic competitiveness against ethical safeguards.","aiGenerated":true,"topicCodes":["foundation_models"],"origin":"promoted"},{"id":"lit-papyshev-yarime-state-role-governing-ai-national-strategies","title":"The state's role in governing artificial intelligence: development, control, and promotion through national strategies","authorsOrOrg":"Gleb Papyshev, Masaru Yarime","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1080/25741292.2022.2162252","finding":"Frames national AI strategies on a development/control/promotion axis, the lens for a promotion-and-leadership national AI posture.","aiGenerated":true,"topicCodes":["sovereign_ai"],"origin":"promoted"},{"id":"lit-gunasekara-responsible-ai-principles-systematic-review","title":"A Systematic Review of Responsible Artificial Intelligence Principles and Practice","authorsOrOrg":"Gunasekara, El-Haber, Nagpal, Moraliyage, Issadeen, Manic, De Silva","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.3390/asi8040097","finding":"PRISMA systematic review (553 of 22,711 screened studies) of responsible-AI principles and practice, including transparency and accountability.","aiGenerated":true,"topicCodes":["transparency"],"origin":"promoted"},{"id":"lit-eguiluz-castaneira-innovation-fundamental-rights-position","title":"Position Paper: If Innovation in AI Systematically Violates Fundamental Rights, Is It Innovation at All?","authorsOrOrg":"Eguiluz Castaneira, Brando, Laukyte, Serra-Vidal","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2511.00027","finding":"Argues regulation is the foundation of AI innovation rather than its brake (accepted, NeurIPS 2025 position-paper track).","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"},{"id":"lit-cset-eo-14179-removing-barriers-tracker","title":"The Executive Order on Removing Barriers to American Leadership in Artificial Intelligence (implementation tracker)","authorsOrOrg":"Center for Security and Emerging Technology (CSET), Georgetown University","evidenceType":"research_institute","evidenceTypeLabel":"Research institute","url":"https://cset.georgetown.edu/article/the-executive-order-on-removing-barriers-to-american-leadership-in-artificial-intelligence/","finding":"Provision-by-provision tracker of EO 14179 implementation and its America's AI Action Plan follow-on (Jul 2025).","aiGenerated":true,"topicCodes":["national_security_carveouts"],"origin":"promoted"},{"id":"lit-fra-bias-in-algorithms-discrimination","title":"Bias in algorithms - Artificial intelligence and discrimination","authorsOrOrg":"European Union Agency for Fundamental Rights (FRA)","evidenceType":"official_grey","evidenceTypeLabel":"Official (grey)","url":"https://fra.europa.eu/en/publication/2022/bias-algorithm","finding":"EU agency report whose predictive-policing feedback-loop simulation shows biased crime data amplifying over-policing of minorities.","aiGenerated":true,"topicCodes":["criminal_justice"],"origin":"promoted"},{"id":"lit-rand-rr233-predictive-policing-perry","title":"Predictive Policing: The Role of Crime Forecasting in Law Enforcement Operations","authorsOrOrg":"Perry, McInnis, Price, Smith, Hollywood (RAND Corporation)","evidenceType":"research_institute","evidenceTypeLabel":"Research institute","url":"https://doi.org/10.7249/rr233","finding":"Foundational study framing four predictive-policing method families; cautions the tools forecast risk, not events.","aiGenerated":true,"topicCodes":["criminal_justice"],"origin":"promoted"},{"id":"lit-hamilton-evaluating-algorithmic-risk-assessment","title":"Evaluating Algorithmic Risk Assessment","authorsOrOrg":"Melissa Hamilton","evidenceType":"peer_reviewed","evidenceTypeLabel":"Peer-reviewed","url":"https://doi.org/10.1525/nclr.2021.24.2.156","finding":"Cross-jurisdiction legal evaluation of pretrial algorithmic risk-assessment tools and their contested fairness and accuracy.","aiGenerated":true,"topicCodes":["criminal_justice"],"origin":"promoted"},{"id":"lit-srivastava-bullock-ai-global-governance-digital-sovereignty","title":"AI, Global Governance, and Digital Sovereignty","authorsOrOrg":"Swati Srivastava, Justin Bullock","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2410.17481","finding":"Theorises digital sovereignty as entangled with institutional control over AI infrastructure and sovereign competence.","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"},{"id":"lit-tubaro-casilli-digital-labour-ai-latin-america","title":"The digital labour of artificial intelligence in Latin America: Argentina, Brazil, and Venezuela","authorsOrOrg":"Tubaro, Casilli, Fernandez Massi, Longo, Torres-Cierpe, Viana Braz","evidenceType":"preprint","evidenceTypeLabel":"Preprint","url":"https://arxiv.org/abs/2502.06317","finding":"Survey and interviews of 911 precarious AI data workers across Argentina, Brazil and Venezuela (the data-colonialism strand).","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"},{"id":"lit-unctad-tir-2025-inclusive-ai-development","title":"Technology and Innovation Report 2025: Inclusive Artificial Intelligence for Development","authorsOrOrg":"UN Trade and Development (UNCTAD)","evidenceType":"official_grey","evidenceTypeLabel":"Official (grey)","url":"https://unctad.org/publication/technology-and-innovation-report-2025","finding":"Flagship inclusive-AI-for-development report: 118 mostly-Global-South countries absent from AI governance; infrastructure, data and skills divides.","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"},{"id":"lit-oecd-rdp147-emerging-divides-ai-transition","title":"Emerging divides in the transition to artificial intelligence (OECD Regional Development Papers No. 147)","authorsOrOrg":"Sandrine Kergroach, Julien Heritier (OECD)","evidenceType":"working_paper","evidenceTypeLabel":"Working paper","url":"https://doi.org/10.1787/7376c776-en","finding":"Working paper measuring how 2023-24 AI adoption reinforces existing divides across places and firms.","aiGenerated":true,"topicCodes":["development_rights_framing"],"origin":"promoted"}]}